Methods For Planning and Retrofit of Energy Efficient Eco-Industrial Parks Through Inter-Time-Inter-Systems Energy Integration

ABSTRACT

Methods of providing enhanced energy efficiency and reduced greenhouse gases for an eco-industrial park with retrofit in mind and eco-industrial park retrofit with retrofit in mind, are provided. An exemplary method includes identifying hybrid inter-time zones inter-area matching solutions through selecting best energy efficient routes, generating technically viable energy efficient eco-industrial parks alternatives, identifying best generation and allocation of energy utilities, and synthesizing a combined heat and power utility system that satisfies the eco-park demands during each time zone as well as rendering its best operating scenario at each specific time-zone. This inter-time-zones inter-area integration can include identifying the best and the second best matching solutions among processes in the eco-industrial park for spatial energy integration and the best and second best matching solutions among all time-zones for temporal energy integration and greenhouse gas emissions reduction for the optimal synthesis or retrofit of eco-industrial parks.

1. RELATED APPLICATIONS

This application is a continuation-in-part of and claims priority to andthe benefit of U.S. patent application Ser. No. 13/858,731, filed onApr. 8, 2013, titled “Systems, Computer Readable Media, and ComputerPrograms for Enhancing Energy Efficiency Via A Systematic HybridInter-Processes Integration,” and U.S. patent application Ser. No.13/858,718, filed on Apr. 8, 2013, titled “Methods For Enhancing EnergyEfficiency Via A Systematic Hybrid Inter-Processes Integration,” whichis a continuation-in-part collectively of and claims priority to and thebenefit of U.S. patent application Ser. No. 12/767,315, filed Apr. 26,2010, titled “System, Method, and Program Product For Synthesizing HeatExchanger Network and Identifying Optimal Topology For Future Retrofit,”which claims priority to U.S. Provisional Patent Application No.61/256,754, filed Oct. 30, 2009, titled “System, Method, and ProgramProduct for Synthesizing Non-Constrained and Constrained Heat ExchangerNetworks and Identifying Optimal Topology for Future Retrofit,” U.S.patent application Ser. No. 13/757,467, filed on Feb. 1, 2013, titled“Methods For Simultaneous Process and Utility Systems Synthesis inPartially and Fully Decentralized Environments,” and U.S. patentapplication Ser. No. 13/757,491, filed on Feb. 1, 2013, titled “Systemsand Computer Programs for Simultaneous Processing Utility SystemsSynthesis in Partially and Fully Decentralized Environments,” whichclaim priority to U.S. Provisional Patent Application No. 61/612,470,filed on Mar. 19, 2012, titled “System, Method, and Computer Program ForSimultaneous Processing Utility Systems Synthesis in Partially and FullyDecentralized Environments,” and U.S. patent application Ser. No.12/480,415, filed on Jun. 8, 2009, titled “System, Program Product, andRelated Methods For Global Targeting of Process Utilities Under VaryingConditions,” and is a continuation-in-part of U.S. patent applicationSer. No. 13/757,467, filed on Feb. 1, 2013, titled “Methods ForSimultaneous Process and Utility Systems Synthesis in Partially andFully Decentralized Environments,” and U.S. patent application Ser. No.13/757,491, filed on Feb. 1, 2013, titled “Systems and Computer Programsfor Simultaneous Processing Utility Systems Synthesis in Partially andFully Decentralized Environments,” which claim priority to U.S.Provisional Patent Application No. 61/612,470, filed on Mar. 19, 2012,titled “System, Method, and Computer Program For Simultaneous ProcessingUtility Systems Synthesis in Partially and Fully DecentralizedEnvironments” each incorporated herein by reference in its entirety. SeeAppendix 1 for a list of related applications.

BACKGROUND OF THE INVENTION

1. Field of the Invention

This invention relates generally to energy management through heatrecovery, and more particularly to systems, computer readable media,program product/code, and methods for providing enhanced energy designand retrofit of, and greenhouse gas reduction for, eco-industrial parksthrough enhanced energy recovery methodologies and system designs.

2. Description of the Related Art

Industrial clusters/symbiosis played a significant role in the economicgrowth of many countries. Recognized by the inventors is that theindustrial ecology concept can promote a new path of local developmentthrough the transition from industrial clusters to Eco-Industrial Parks(EIPs). Further recognized is that this can be accomplished byexploiting common features of both models such as, for example, thegeographic proximity of time-dependent and non-dependent plants and thenon-industrial community, such as malls, hospitals, hotels, housingcompounds, schools and so on. Accordingly, also recognized is thatimplementing the eco-industrial parks' principles in an existingindustrial cluster or in the planning of new ones, represents asignificant opportunity for its revitalization. For example,eco-industrial parks could potentially exploit synergies from industrialclusters and non-industrial activities to create new production modelsin which the economic and environmental dimensions are symbiotic.

Prior eco-industrial parks' key to success has been a sequence ofindependent economically driven actions. Such evolutionary patternfollowed to date by countries like Denmark, for example, may not beeasily transferred from conventional industrial complexes toeco-industrial parks locations and/or Greenfield development.Accordingly, recognized by the inventors is the need for and benefit ofa holistic/revolutionary approach in addressing the problem, using novelmethodologies and tools, followed by an evolutionary approach inimplementing necessary modifications in either contaminated Brownfieldsor in the planning/design of Greenfields.

The applicable literatures show that it is very difficult, with thecurrent state-of-art methods and tools, to manufacture eco-industrialparks to work from scratch. First, there should be the basic ingredientsin place, namely the desire of plants/firms/communities to activelyparticipate/cooperate and the correct membership/mix and structure offirms. These basic ingredients can then be enhanced and improved uponwith the correct support structure in place. The inventors recognizethat a significant factor that can enhance the success of eco-industrialpark is the presence of a large company which acts as a magnet for othercompanies. The inventors also recognize that the willingness to make theeffort to determine the best connections among different industrialplants/firms and its surrounding communities in an eco-industrial parkcan be another significant factor in developing a successfuleco-industrial park or transforming conventional industrial complexes toeco-industrial parks. Specifically, the material and energy flows'relationship among the different members in the alliance of plants/firmscan permit establishing optimal linkage to form a fruitful inter-dynamicstructure. If such structure does not exist, a successful eco-industrialpark may not be able to be realized. The inventors further recognizedthat the emphasis for the eco-industrial park should be on a systemapproach, rather than focusing on specific streams. Accordingly,recognized is the need for systems, computer readable medium, programproducts/code, and methods which capitalize on such recognitions.

The sustainability concept is considered to have four dimensions, namelysocial, environmental, economic, and institutional. It is understood tobe the improved management of natural resources within a businesssetting to provide economic and social benefits to the business and itssurroundings. Eco-industrial parks can serve a significant role inrealizing the economic, environmental and social benefits both toindividual plants/companies as well as to network of plants/firms. Assuch, eco-industrial parks have been publicized as a means of reducingenvironmental damage through reduced waste, based on the literature casestudies. Studies have shown that eco-industrial parks can have a numberof benefits at different levels. The desire to attain financial gainirrespective of the environmental benefits, however, has historicallybeen the major driving factor for the creation of most eco-industrialparks.

Besides other objectives, the conventional system concept oftransitioning industrial complexes to eco-industrial parks and theplanning and synthesis/design of the new ones for energy efficiencymaximization and energy-based GHG emissions reduction, is the transferof waste heat from one plant/firm to a nearby another. In other words,each plant/facility/firm in the eco-industrial park alliance allows theusage of its waste energy to be used by another adjacentplant/facility/firm. The energy waste of one company is used partiallyor totally in another adjacent one. Through waste integrationcooperation, adjacent plants can save transportation costs and energydegradation during transit.

There are essentially three recognized approaches for transitioningindustrial complexes to eco-industrial parks and the planning andsynthesis/design of the new ones to attain the objectives of energyefficiency maximization and energy-based GHG emissions reduction, amongothers. The first approach is the ad hoc method which uses an obviouswaste heat stream from a power plant in a nearby process, for example.This method, however, is not systematic and is far from efficient.

The second approach is the total site targeting method, which is basedon the pinch technology, the most widely used to date in literature.This method allows waste heat from processes to be used as a source ofheat in other processes. The waste heat sources are converted to steam,which through a steam system infrastructure, is utilized to pass theheat to processes that are in heat deficit. To identify the externalheating and cooling requirements of a group of individual plants to besatisfied by a central utility system, for each of the individualplants, a thermal integration of its hot streams to be cooled and coldstreams to be heated is performed using each individual plant's grandcomposite curve. The temperature/enthalpy data from respectiveindividual plant is then extracted from the plant.

The grand composite curve defines each plant's thermal heat deficiencyand thermal heat surplus after intra-plant heat integration. Thecollection of grand composite curves of the whole site are then used tographically add all thermal deficiencies to draw the total site heatingdemand curve, and add all thermal surpluses to draw the total sitecooling demand curves. The two curves are then superimposed on one graphwith the existing and/or suggested steam generation levels and steamsupplying levels to find the minimum total site external energyutilities requirement and naturally best indirect inter-plants thermalintegration. In this method, intra-integration is accomplished first.Thereafter, any remaining waste heat (below pinch streams) of the plantis shared with other parks' members. The inventors recognize thismethodology to be a reactive form of cooperation rather than a proactiveform. Also, recognized is that this methodology results in a mismatch innumber of steam levels required for eco-industrial park users ingeneration and utilization, which translates to undesirable energy loss.Further, while in literature, this method in its application is said tobe able to address both time non-dependent and time dependent sitesprocesses, the use of time as an optimization variable for hybridinter-time-inter-systems energy integration is ignored.

Therefore, recognized by the inventors is the need for a methodology:that can accomplish inter-time zone and systems integration first; thatcan share the waste heat of multiple processes within each plant witheach other plant; that can match the number of steam levels; thatutilizes time as an optimization variable for hybridinter-time-inter-systems energy integration; and that can modified timezone or zones boundaries/duration.

The third approach uses the mathematical programming method, which usessimplistic assumptions to be able to model whole city’ industrial andnon-industrial processes without resulting in a mathematicallyintractable problem. The inventors are open to the possibility that themathematical programming method could, theoretically speaking, find bestmass and energy integration among its members, and design the wholeeco-industrial park energy utility system accordingly. Currently,however, there is no public domain literature describing how to use suchapproach in the retrofit or in the planning of new energy efficienteco-industrial park applications.

The state of-the-art software for transitioning industrial complexes toeco-industrial parks and for the planning and synthesis/design of thenew ones for energy efficiency maximization and energy-based GHGemissions reduction, among other objectives, are extremely limited andalmost non-existent. The most famous one is the Apentech Co. Total Sitecommercial software. Other decision support software for generaleco-industrial park planning, namely “FaST”, “DIET” and “REaLiTy”, aredatabase software with linear programming capability. These software areessentially focused on material exchange and only address very obviouswaste heat exchange, where a waste heat stream in one plant/powerstation is used in other eco-industrial parks' plants.

Recognized by the inventors is that proper planning of neweco-industrial parks, and the transformation of conventional industrialcomplexes to an eco-industrial park, can bring significant value toenergy efficiency. Further, recognized by the inventors is that thetransition of an industrial complex's energy systems to, or synthesis ofeco-industrial parks containing time dependent and non-dependentprocesses and tasks (referred to as industrial symbiosis), is a hugemulti-variable multi-dimensional optimization problem in which the totaleco-industrial park network depends on a factor as small as a singlestream condition and as big as the whole park/city functionality. Alsorecognized by the inventors is that integration among multipleindustrial and non-industrial plants/processes in adjacent geographicallocations can bring in more degrees of freedom to optimize the “wasteenergy recovery,” and consequently, presents a new horizon for radicalenergy-based GHG emissions reduction.

Further recognized by the inventors is the need for a methodology forthe simultaneous inter-time zones-inter-systems energy integration inindustrial symbiosis where non-industrial community is also included, toattain new levels of energy saving and GHG emissions reduction usinghybrid methods of integration. Additionally recognized is the need for ahybrid methodology that systematically looks to all options together andfinds best combinations out of the available solutions package, whilesimultaneously considering both inter-time-zones and inter-systemsenergy integration.

SUMMARY OF THE INVENTION

Many of the reasons hindering the application of simultaneousinter-process integration among several processes, for better energyconsumption cost reduction and less energy-based GHG emissions, are insome cases valid. However, according to various embodiments of theinvention, most of them can be addressed in a novel cost-effective wayto enable wider adaptation. The adaptation of inter-time-inter-systemsenergy integration in industrial cities to date is not systematicallypracticed. Additionally, since the emanation of the pinch technology andits evolution to pinch analysis technique for process synthesis, thedirect inter-processes integration has been considered impractical. Theinventors have recognized that old arguments such as that: the processessometimes have different start up and shut down times; the processes canwork at partial loads; the processes can have seasonal changes in itsconditions; the utility systems, heaters and HEN capital may not bereduced due to changes in processes schedule and operation philosophy;the disturbance in one process can propagate to another one if they areintegrated which make the process difficult to control; thedistance-time/velocity lags affect the controllability of processes; thegeographical distances among processes will cost energy in pumping orcompression and capital in piping, pumping, and compression; the concernthat safety might be impacted due to the travel of a fluid from onehazardous area to another; and the fear of leakage, and so on, which arevery common to plant engineers, can now have cost-effective solutions,which can be considered during matching phase.

In view of the foregoing, various embodiments of the present inventionadvantageously provide systems, computer readable media, programproduct/code, and methods of systematically providing enhanced energyefficiency and reduced greenhouse gases for an eco-industrial parkthrough inter-time-inter-system energy integration. Various embodimentsof the present invention advantageously provide systems, computerreadable media, program product/code, and methods that achieve newlevels of energy consumption and energy-based GHG emissions reductionvia radical energy efficiency improvement of eco-industrial parksplanning and/or retrofit using hybrid inter-system-inter-time-zonesenergy integration solutions. Such solutions can advantageously includesystematic hybrid inter-processes integration. Various embodiments ofthe invention provide a holistic/revolutionary approach in addressingthe problem, using novel methodologies and tools, followed by anevolutionary approach in implementing necessary modifications in eithercontaminated Brownfields or in the planning/design of Greenfields.

Various embodiments provide a methodology for the simultaneousinter-time zones-inter-systems energy integration in industrialsymbiosis where non-industrial community is also included to attain newlevels of energy saving and GHG emissions reduction using hybrid methodsof integration. Various embodiments use a hybrid methodology thatsystematically looks to all options together and that finds the bestcombinations out of the available solutions package while simultaneouslyconsidering both inter-time-zones and inter-systems energy integration.Various embodiments of the invention also or alternatively address theenergy component of eco-industrial park via novel system approach,computer readable medium, program products/code, and methods whichprovide for the retrofit or synthesis of efficient eco-industrial parks'energy systems symbiosis.

Various embodiments of the invention provide systems, computer readablemedium, program product/code, and methods for enhancing energyefficiency of the eco-industrial park mega-problem's representation,energy targeting for industrial and non-industrial processes/activities,inter-time-zones-inter-processes/activities energy integration, and besttemporal and spatial matching among energy-dependent processes andactivities. All industrial and non-industrial processes/activities, hotstreams to be cooled and cold streams to be heated, can be representedin one time-temperature interval graph using a new composite curvesbuilding method where the problem-wide pinch point(s) is defined andoptimal pinch temperature is identified, and time and space zone, block,facility, process unit, and or stream controlling pinch point locationis found. Zone(s), block(s), facility(s), process(s) unit and stream(s)having high impact on the waste energy recovery problem are located. Agraphical technique can be used to identify minimum number of directmatches/connections among time and space zones or blocks or facilitiesor processes. The graphical technique can include utilization of atemperature-duty diagram and a time-temperature-duty diagram. Where thecurrent state-of-art is only adapting direct or indirect spatialintegration, but not both, and/or where the current state-of-art is onlyadapting indirect integration using steam system or hot oil system, butnot both together, various embodiments of the invention provide hybridmethodologies. Various embodiments of the invention address the combinedheat and power system planning for the whole eco-industrial park in amulti-time-period approach while considering simultaneously bestinter-time-zones-inter-systems energy integration applications' options.

An example of an embodiment of a method of providing enhanced energyefficiency and reduced greenhouse gases for an eco-industrial parkthrough application of spatial and temporal waste heating and coolingenergy integration, can include the steps of identifying the functionalareas for an eco-industrial park, and identifying significant heatingand cooling tasks for each significant time-dependent andnon-time-dependent industrial and non-industrial activity within theeco-industrial park. The functional areas include both a plurality ofindustrial functional areas and one or more non-industrial functionalareas, in adjacent geographical locations. Each of the plurality ofindustrial functional areas typically include a plurality of spatialzones, a plurality of blocks, a plurality of facilities, a plurality ofplants, and a plurality of batch and continuous process units, and atleast one, but more typically multiple hot process streams to be cooled,and/or at least one, but more typically multiple cold process streams tobe heated. The one or more non-industrial functional areas can includeone or more housing compounds, one or more hospitals, one or morelaundry facilities, and one or more facilities having large capacitydishwashing units, which include one or more hot waste streams and/orone or more cold streams. The non-industrial functional areas cancontain new sources of hot or cold streams, which advantageously providean untapped potential in thermal integration.

The step of determining one or more inter-time zone thermal energyintegration targets can include analyzing the duration of the pluralityof time zones as an optimization variable. According to an embodiment,the boundaries of the plurality of time zones can be defined by asmallest heating or cooling time duration for any significant activityin the eco-industrial park under analysis. Time zone or zones boundariescan be modified, for example, via control flow rates and/ororchestrating batch tasks (industrial and non-industrial) timing andduration. Flow rates can be controlled using, for example, variablespeed drivers. The steps of determining one or more inter-time zonethermal energy integration thermal targets and intra-time zone thermalenergy integration thermal targets can include the steps of identifyingtotal supply and demand thermal energy loads at each of a plurality oftemperature intervals, identifying inter-time zone surplus thermalenergy load between each of the plurality of time zones at each of theplurality of temperature intervals, identifying total supply and demandthermal energy loads at each of the plurality of time zones at each ofthe plurality of temperature intervals, and identifying a thermal energyload to be integrated via inter-time zone thermal energy integration andintra-time zone matching. The steps can also or alternatively includeidentifying total supply and demand at each temperature interval,identifying the supply and demand and surplus of each functional area,and identifying the global minimum heating and cooling needs for thedependent and non-time dependent industrial and non-industrialactivities.

The method can also include the step of determining one or moreinter-time zone thermal energy integration thermal targets andintra-time zone thermal energy integration thermal targets responsive toor otherwise based upon the identified functional areas and identifiedsignificant heating and cooling tasks, and identifying one or moreinter-time zone thermal energy integration matching solutions across aplurality of time zones to substantially satisfy a thermal load or loadsto be integrated via inter-time zone thermal energy integrationresponsive to her otherwise based upon. The step of identifying can beperformed responsive to or otherwise based upon the determined one ormore inter-time zone thermal energy integration thermal targets and oneor more intra-time zone thermal energy integration thermal targets. Thisstep can be performed prior to performing intra-time zone thermal energyintegration matching. This can advantageously provide the least possiblequality degradation by not removing pockets that result from performingintra-time zone integration prior to performing inter-time zoneintegration.

The step of identifying the one or more inter-time zone thermal energyintegration matching solutions can include generating the matchingsolutions based upon thermal loads determined using inter-time zonethermal energy integration in conjunction with inter-area/system thermalenergy integration within and across the respective time zones, and/orperforming inter-time zone thermal energy integration matching, whichcan include temporally and spatially matching batch process streams withbatch process streams and batch process streams with continuous processstreams, and/or which can be performed while simultaneously consideringboth inter-time zones and inter-area thermal energy integration. Thematching can also or alternatively include identifying a plurality ofthe functional areas to be included and one or more of the functionalareas to be excluded in the matching solution.

The identifying step can also or alternatively include identifying best,second best, third-best, fourth best, and so on, matching solutions fromthe one or more potential inter-time zone thermal integration matchingsolutions. One of the matching solutions can be selected that eithersubstantially satisfies an optimal one of the one or more inter-timezone thermal energy integration thermal targets and/or a desired levelof one or more energy targets for heating utility, cooling utility, orboth heating utility and cooling utility selected by a decision-maker.

The step of identifying one or more inter-time zone thermal energyintegration matching solutions can also or alternatively includematching waste heat of multiple hot process streams within eachfunctional area with multiple hot process streams of each otherfunctional area of a plurality of functional areas. This can beperformed for each of a plurality of different steam levels required bytasks/activities within the functional areas. This step can also oralternatively include performing inter-time zone thermal energyintegration matching while simultaneously considering both inter-timezone and inter-area integration. The matching can include performinghybrid matching techniques such as, for example, direct and indirectarea integration, hot-to-hot process-to-process matching, cold-to-coldunit process-to-process matching, and process identities switching, andcan include performing process stream rescheduling, performing processenergy storage, and performing process stream heat capacity flowratemanipulation using variable speed drivers.

The steps can also or alternatively include generating one or moretechnically viable eco-industrial park heat exchange system designalternatives responsive to the identified one or more inter-time zonethermal energy integration matching solution and/or generating at leastone technically viable energy efficient eco-industrial park alternativethat satisfies the eco-industrial park thermal energy and steamutilities demands for the plurality of time zones as well as rendering acorresponding approximately optimal operating scenario at each specifictime-zone.

The method can also or alternatively include identifying the media ofthe thermal load to be integrated via inter-time zone thermal energyintegration, e.g., thermal energy storage, rescheduling of activities orprocess streams, and changing of process stream flow rates, andidentifying one or more intra-time zone thermal energy integrationmatching solutions for each of the plurality of time zones and across aplurality of the functional areas having one or more tasks operatingwithin the respective time zone when having more than one functionalarea associated therewith. The step of identifying one or moreintra-time zone thermal energy integration matching solutions caninclude identifying best and the second best matching solutions amongthe hot and cold process streams in the eco-industrial park for spatialenergy integration, and identifying best and second best matchingsolutions among each of the plurality of time-zones for temporal energyintegration and greenhouse gas emissions reduction for optimal synthesisor retrofit of the eco-industrial park. This step can also oralternatively include identifying functional areas to consider forintegration and others to neglect as having an in substantial energyvalues.

The method can also include the step of generating a plurality oftechnically viable energy efficient eco-industrial park alternativesthat satisfies eco-industrial park utilities demands during each of thetime zones as well as rendering a corresponding approximately optimaloperating scenario at each specific time-zone. This step can includeidentifying a scheme of inter-area integration including direct,indirect or hybrid inter-area integration, and when either indirect orhybrid are utilized, identifying indirect medium, the indirect mediumcomprising water, steam, hot oil, or a combination thereof. The solutioncan account for hot and/or cold process streams having different startup or shut down times, that work intermittently at partial loads, orthat have seasonal dependent operating conditions.

The method can also or alternatively include identifying one or morebest energy and greenhouse gas emission reduction targets,systematically identifying when direct inter-time integration is bestutilized and is the only option to reach the best energy and greenhousegas emissions reductions' targets, and systematically identifying whenindirect intra-time integration alone can be used to reach the bestenergy and greenhouse gas emissions reduction targets.

The method can also or alternatively include the steps of extractingoperational data for the plurality of significant heating and coolingtasks, the operational data comprising duration, process stream initialtype, supply temperature, target temperature, and heat capacity flowrate, constructing a virtual time-space schematic for the eco-industrialpark heating and cooling tasks to identify time zone boundaries, andproviding a Time-Temperature-Duty-Diagram to establish a functional areasupply-demand cascade from heating and cooling tasks respectively ateach of a plurality of temperature intervals. The steps can furtherinclude calculating a total supply and demand at each temperatureinterval, the step of calculating comprising cascading the functionalareas supply and demand in time, calculating one or more of thefollowing: inter-time zones energy load storage, reschedulingrequirements, and stream flowrate modifications among each of theplurality of time zones for the eco-industrial park, and calculatingglobal minimum heating and cooling needs for the dependent andnon-dependent industrial and non-industrial activities of theeco-industrial park.

According to an embodiment of the method, the step of identifying one ormore inter-time zone thermal energy integration matching solutions canalso or alternatively include constructing a virtual problem widetime-temperature duty diagram. The step of constructing can includeforming a global Cold Composite Line (gCCL) summarizing heating energyrequirements for substantially all significant zones, blocks,facilities, plants and processes' streams in each of a plurality of timezones at each of a plurality of temperature intervals, and forming aglobal Hot Composite Line (gHCL) summarizing cooling energy requirementsfor substantially all the zones, blocks, facilities, plants andprocesses' streams in each time zone at each of the plurality oftemperature intervals. The steps can also include displaying aproblem-wide pinch location or interval, displaying indicia of coldcomposite and hot composite thermal loads above the problem-wide pinchtemperature for each individual time zone, displaying indicia of a coldcomposite and hot composite thermal loads below the problem-wide pinchtemperature for each individual time zone, displaying indicia of totalsurplus heating load for each time zone for above the problem wide pinchtemperature and for below the problem wide pinch temperature, displayingindicia of a global cooling energy utility requirement, displayingindicia of total surplus cooling load for each time zone for above theproblem-wide pinch temperature and for below the problem-wide pinchtemperature, and displaying indicia of a global heating energy utilityrequirement.

According to an embodiment of the method, the step of identifying one ormore inter-time zone thermal energy integration matching solutions canalso or alternatively include the step of performing hybrid inter-timezone inter-area thermal energy integration matching. The matching caninclude the steps of predefining a global cold composite line accountingfor heat energy requirements for substantially all significant zones,blocks, facilities, plants and processes' streams comprised by theplurality of functional areas in each of a plurality of time zones ateach of a plurality of temperature intervals, and predefining a globalhot composite line accounting for waste cooling energy for substantiallyall the zones, blocks, facilities, plants and processes' streams in eachtime zone at each of the plurality of temperature intervals. Thematching can also include the steps of identifying thermal loads to beintegrated via intra-time integration and inter-time integration,conducting inter-time zone energy matching, defining media of thethermal load to be integrated via the inter-time zone thermal energyintegration, and conducting intra-time zone intra-area energy matchingfor each of the plurality of time zones. The conducting step can includeinitiating the intra-time intra-area matching via de-lumping of eachpredetermined time zone specific global cold composite line and eachpredefined time zone specific global hot composite line into itsfunctional area structures from largest to smallest, and conducting theintra-time intra-area matching.

According to an embodiment of the method, the steps can also oralternatively include determining global minimum heating energy utilityand global minimum cooling energy utility requirements under allreasonably probable combinations of process-specific modifications andstream-specific ΔT_min in an acceptable user defined range across spaceand time, locating problem wide pinch interval and pinch locationcontrolling stream or streams, determining energy targets for inter-timeinter- and intra-space energy integration and intra-time inter- andintra-space energy integration, receiving decision maker selectionidentifying desired level of energy targets for one or more of thefollowing: heating utility, cooling utility, and both heating andcooling utilities, and receiving user input of absolutely constrainedand forbidden functional area and process streams matching whereby arespective thermal load must be satisfied via indirect integration. Thesteps can also include collapsing operational data intervals whenoperational data is provided in interval form to locate the problem widebest for desired pinch temperature, the pinch-temperature locationcontrolling process, and the best process stream changes as well asstreams-specific ΔT_min in the acceptable user defined range. In thisembodiment, the step of identifying one or more inter-time zone thermalenergy integration matching solutions can include determining one ormore best possible matches among the time zones and the functionalareas.

According to an embodiment of the method, the steps can also oralternatively include generating a plurality of technically viableenergy efficient eco-industrial park alternatives that satisfieseco-industrial park utilities demands during each of the time zones aswell as rendering a corresponding approximately optimal operatingscenario at each specific time-zone. According to an aspect of thisembodiment, the step of generating one or more technically viable energyefficient eco-industrial park alternatives can include identifying bestgeneration and allocation of steam energy utilities, and synthesizingthe combined heat and power utility system that satisfies theeco-industrial park utilities demands during each of the time zones aswell as rendering its best operating scenario at each specifictime-zone.

According to another aspect, the step of generating can also oralternatively include calculating required steam supply and demandlevels and loads for the plurality of functional areas, establishing avirtual functional area steam supply-demand cascade in space from steamsupply and demand loads respectively at each a plurality of steamlevels, calculating total supply and demand loads at each steam levelresponsive to the cascade of the functional areas steam supply anddemand in space, defining functional area arrangements which minimizesteam transportation, and identifying amounts of steam to be transferredfrom one functional area to another to achieve global minimum steamdemand before steam letdowns.

According to another aspect, the step of generating a plurality oftechnically viable energy efficient eco-industrial park alternativesincludes the step of performing a domino affect low-pressure steamsharing targeting process. This process can include the steps ofallocating low-pressure steam to functional areas in a mosaic startingwith a central power plant or main cogeneration plant then followed byfunctional areas arranged in the form of demand supply demand and endingby functional area demand. In such configuration, steam is beingtransferred from one functional area to the next functional areaprimarily or completely only to avoid long distances and steamcondensation. Correspondingly, a number of the functional areas act as aconduit to pass steam from a supplying functional area to anotherfunctional area without requiring steam from the supplying functionalarea. The steps also include highlighting in-process modifications thatcan be performed to enhance process or functional area capability inproducing more steam or whose status can be changed from demanding tosupplying or vice versa, and arranging the functional areas by theirgeographical locations to substantially reduce steam travel distancesand steam condensation.

The economics of industrial production, the limitations of global energysupply, and the realities of environmental conservation are an enduringconcern for all industries. The majority in the world scientificcommunities believe that the world's environment has been negativelyaffected by the global warming phenomenon due to the release ofgreenhouse gases (GHG) into the atmosphere. Accordingly, variousembodiments of the invention advantageously include systems, computermedium, program product/code, and methods for systematic targeting forhybrid, direct and indirect, inter-time-zones-inter-systems energyintegration in eco-industrial parks planning and retrofit that cancreate new opportunities for energy conservation beyond that currentstate-of-art in eco-industrial parks, which mostly depend only onintra-process integration and indirect inter-processes integration usingsteam or hot oil systems whereby waste energy is not optimallyrecovered. Various embodiments identify, systematically, the leastnumber of temporal and spatial direct inter-processes integrationconnections which render best impact on waste energy recovery beforeaddressing the decision of whether or not to resort to indirect processintegration methods using steam, hot oil, and tempered hot watersystems.

Various embodiments provide a systematic methodology for enhancingenergy efficiency and GHG emission reduction in the development of neweco-industrial parks due to energy efficiency optimization beyond whatis possible to date using state-of-art technologies. This can beaccomplished, for example, via hybrid inter-time-zones-inter-systemsintegration that overcomes technical problems, such as ΔT_minconstraints and others such as, for example: economics-of-scalesconstraints, capital availability constraints in standalonecompanies/plants/processes and so on, during the retrofit or planning ofeco-industrial parks. Various embodiments also or alternatively providea systematic methodology for enhancing energy efficiency beyond what ispossible to date in the retrofit or planning of eco-industrial parksusing state-of-art technologies, accomplished, for example, via thesimultaneous hybrid inter-time-zones-inter-systems integration thatovercomes the problem of intra-units/processes partially andfully-forbidden matches' constraints and the problem of ΔT_minconstraints in standalone units and processes that are having a negativeimpact on waste energy recovery.

The hybrid inter-time-zones-inter-systems integration can be performedunder all possible industrial and non-industrial intra-processes' and/oractivities structures and parameters as well as operating conditions'scenarios changes while using streams' specific ΔT_min. Thesteps/operations performed to obtain the hybridinter-time-zones-inter-systems integration can include identifying whichplant would be ideal as an ambassador and which stream(s) would be idealas an ambassador(s), and/or can employ hot-to-hot and cold-to-coldmatching and streams switching techniques for partially and/or fullyforbidden matches. The steps/operations can also or alternativelyprovide for use of steam, hot oil, tempered water and a mix of all ofthem, and can define the type of indirect integration in both time(temporal) and space (spatial) and its desired thermal load. Thesteps/operations can also or alternatively include identifying the besteco-industrial parks alliance of members via defining what is best, thesecond best, third-best, and so on, in inter-time-zones-inter-systemsdirect integration. The integration can be performed withretrofitability-in-mind of each unit, process, facility, block and zonefor the sake of more energy conservation, via finding both the currentand the future problem's optimal pinch, and conducting matching for thecurrent system and future system. The steps can also or alternativelyidentify situations where inter-time-zones-inter-systems directintegration is the only option to reach desired energy and GHG emissionsreduction targets. An example of direct inter-time zone integrationincludes utilization of storage tanks, and manipulating or delaying flowstreams, among others recognized by one of ordinary skill in the art.

Various embodiments of the invention advantageously include systems,computer readable medium, program product/code, and methods which renderradically enhanced energy efficiency and reduced energy-based GHGemissions, beyond what is conventionally possible, through the synthesisand retrofit of industrial complexes to eco-industrial parks. Thisachievement can be provided through use of a new approach or approachesin which members go beyond exchanging their wastes, to a new level ofcooperation in which each member (e.g., facility, housing compound,mall, hospital and so on) in the eco-industrial park’ alliance performswaste heat, power, and utility resource import, export, or exchange asnecessary for the mutual benefit of the whole alliance. According to theapproaches, each member is designed to, and makes the necessary changesin its business-as-usual design and/or operationstrategies/philosophies, to advance energy efficiency and GHG emissionsreduction.

Various embodiments of the invention advantageously can create newopportunities to energy consumption and GHG emissions reduction beyondwhat is possible to date via novel hybrid inter-systems inter-timeenergy integration technique to overcoming the problems of currentintra-system intra-time energy integration constraints, which negativelyimpact the possibility of enhancing waste energy recovery. According toone or more embodiments, this can be accomplished using, simultaneously,all possible intra-processes intra- and inter-time structures andparameters conditions' changes, stream specific minimum temperatureapproach (ΔT_min), direct and indirect inter-systems integration,hot-to-hot process-to-process matching, cold-to-cold unitprocess-to-process matching, process identities switching (hybridtechniques), rescheduling, energy storage, and heat capacity flowratemanipulation using variable speed drivers, for present requirements,while considering future retrofit for more energy conservation to reachbest energy and GHG emissions targets. Various embodiments of theinvention advantageously provide for systematically identifying whendirect inter-time integration is best utilized and is the only option toreach the best energy and GHG emissions reductions' targets, and whenindirect intra-time integration alone can be used to reach best energyand GHG emissions reduction targets.

Various embodiments of the invention advocate a differentapproach/eco-industrial park concept where industrialactivities/companies and non-industrial activities form “total communitysymbiosis,” while conventional approaches, in contrast, advocate onlythe creation or retrofitting of industrial zones where waste orby-products of one company are used as resources by another company. Oneor more embodiments of the invention address a energy consumption andgreenhouse gas reduction methodology that is wider and different thanthat addressed by the current-state-of-art. For example, one or moreembodiments seek to achieve best synergy, which is not addressed byconventional systems, whereas, conventional systems employ anintegration methodology whereby “one facility's energy waste becomesanother facility's energy supply.” Instead, according to an exemplaryimplementation, the “best synergy” refers to an optimal system design ofthe whole eco-industrial park energy system simultaneously, notsequentially.

Various embodiments of the invention advantageously can render moredegrees of freedom for radical energy efficiency and a new problemrepresentation for initial solutions generation, and can render hybridintegration solutions designs with retrofit in mind or retrofit withretrofit in mind. Various embodiments can utilize a holistic systematicapproach including advanced matching, e.g., cold-cold, hot-hot, streamsswitching identity, and streams changing identity to save quality andhelp others get more benefit. Various embodiments can employprocess-specific changes, energy storage and transfer forinter-time-dependent and/or inter-space-dependent integration,process-specific rescheduling in the context of the overall system, andprocess-specific FCp changes for time-dependent and continuous processesusing variable speed drivers. Various embodiments can provide betterdata extraction resulting from the inclusion of new types of streamssuch as waste streams in housing compounds and hospitals, washingmachines, dish washers and so on. Various embodiments can employintra-integration of time-dependent systems, and can provide the leastpossible quality degradation by not removing integration pockets, whichresult from performing intra-time zone integration prior to performinginter-time zone integration. Integration pockets are produced, forexample, when intra-process integration is conducted and hot and coldstreams in heat exchangers are matched using a temperature differencethat is higher than the desired minimum. Various embodiments can employsimultaneous consideration of utility and processes design or retrofit,integration in time and space simultaneously, and inclusion ofindustrial and non-industrial systems in the problem boundary.

Various embodiments of the invention can provide targeting for bestcandidate and the second best alternative and so on for any number ofzones, blocks, facilities, plants processes and streams as well as anynumber of time intervals for time-dependent processes. According tovarious embodiments, solution alternatives can include best candidate(s)for system symbiosis, best process-specific conditions modifications andrescheduling, best matches, batch-with-batch and batch-with-continuousmatching, in time or in space or both, best utility synthesis notlimited to a given utility design, and best utility operating scenariofor each time interval.

BRIEF DESCRIPTION OF THE DRAWINGS

So that the manner in which the features and advantages of theinvention, as well as others which will become apparent, may beunderstood in more detail, a more particular description of theinvention briefly summarized above may be had by reference to theembodiments thereof which are illustrated in the appended drawings,which form a part of this specification. It is to be noted, however,that the drawings illustrate only various embodiments of the inventionand are therefore not to be considered limiting of the invention's scopeas it may include other effective embodiments as well.

FIG. 1 is a schematic diagram of an eco-industrial park targeted forinter-time inter-systems energy integration according to an embodimentof the present invention.

FIG. 2 is a schematic block diagram of a system to target for enhancedenergy efficiency and greenhouse gas reduction for eco-industrial parkaccording to an embodiment of the present invention.

FIG. 3 is a block flow diagram illustrating the interconnection betweenmajor processes/program modules according to an embodiment of thepresent invention.

FIG. 4 is a schematic diagram of a central multi-generation utilitysystem in synergy with a mega industrial community including industrialand non-industrial according to an embodiment of the present invention.

FIG. 5 is a symbol key for the utility system shown in FIG. 4representing plants and units, among others, labeled A-T according to anembodiment of the present invention.

FIG. 6 is a block flow diagram illustrating a time-dependent processesenergy targeting and initial solutions' finding model according to anembodiment of the present invention.

FIG. 7 is a data table and corresponding graph providing an exemplarydisplay of the tabular data according to an embodiment of the presentinvention.

FIG. 8 is a time duty diagram illustrating the tabular data of FIG. 7according to an embodiment the present invention.

FIG. 9 is a temperature time duty diagram illustrating the tabular dataof FIG. 7 used for visualizing inter-time zones integration according toan embodiment of the present invention.

FIG. 10 is a graphical illustration of a populated time-dependentprocesses energy targeting model according to an embodiment of thepresent invention.

FIG. 11 is a graphical illustration of the model of FIG. 10 highlightedfor rotation according to an embodiment present invention.

FIG. 12 is a graphical illustration of the model of FIG. 11 afterrotation according to an embodiment of the present invention.

FIG. 13 is a graphical illustration of a temperature time duty diagramused for inter-time zones solutions' finding according to an embodimentof the present invention.

FIG. 14 is a graphical illustration of the time-temperature duty-diagramof FIG. 13 illustrating an exemplary matching scenario according to anembodiment the present invention.

FIG. 15 is a flow diagram illustrating a conventional solution obtainedutilizing the graphical model of FIG. 12 according to an embodiment ofthe present invention.

FIG. 16 is a flow diagram illustrating a conventional solution obtainedutilizing the graphical model of FIG. 12 according to an embodiment ofthe present invention.

FIG. 17 is a flow diagram illustrating a conventional solution obtainedutilizing the graphical model of FIG. 12 according to an embodiment ofthe present invention.

FIG. 18 is a block flow diagram illustrating execution steps for amathematical program model according to an embodiment of the presentinvention.

FIG. 19 is a graphical illustration of a domino effectlow-pressure-steam “sharing” targeting method according to an embodimentof the present invention.

FIG. 20 is a graphical illustration of a conventional method ofobtaining low-pressure steam.

FIG. 21 is a graphical illustration of a conventional method ofobtaining low-pressure steam.

FIG. 22 is a graphical illustration of a conventional method ofobtaining low-pressure steam.

FIG. 23 is a graphical illustration of a conventional method ofobtaining low-pressure steam.

FIG. 24 is a graphical illustration of the domino effect low-pressuresteam sharing for results comparison with FIGS. 22 and 23, according toan embodiment of the present invention.

FIG. 25 is a graphical illustration of a model used for formulating asharing scenario of multi-levels multiple facilities steam targetingaccording to an embodiment of the present invention.

FIG. 26 is a graphical illustration of a non-sharing scenario ofmulti-levels multiple intra-facilities steam calculation.

FIG. 27 is a graphical illustration of a sharing scenario ofmulti-levels multiple inter-facilities steam targeting calculationaccording to an embodiment of the present invention.

FIG. 28 is a graphical illustration of a data table for aneco-industrial park data extraction example according to an embodimentof the present invention.

FIG. 29 is a graphical illustration of an energy consumption and pinchlocation calculation webpage form according to an embodiment of thepresent invention.

FIG. 30 is a graphical illustration of an energy consumption and pinchlocation calculation webpage form restricted to standalone batch plantenergy targeting calculations according to an embodiment of the presentinvention.

FIG. 31 is a graphical illustration of an energy consumption and pinchlocation calculation webpage form restricted to standalone housingcompound energy targeting calculations according to an embodiment of thepresent invention.

FIG. 32 is a graphical illustration of an energy consumption and pinchlocation calculation webpage form restricted to standalone hospitalcompound energy targeting calculations according to an embodiment of thepresent invention.

FIG. 33 is a graphical illustration of an energy consumption and pinchlocation calculation webpage form restricted to standalone chemicalprocess I (continuous) energy targeting calculations according to anembodiment of the present invention.

FIG. 34 is a graphical illustration of an energy consumption and pinchlocation calculation webpage form restricted to standalone chemicalprocess II (continuous) energy targeting calculations according to anembodiment of the present invention.

FIG. 35 is a graphical illustration of a time interval graph for aneco-industrial park time space zones example according to an embodimentof the present invention.

FIG. 36 is a graphical illustration of an eco-industrial park time zonesstreams data table according to an embodiment of the present invention.

FIG. 37 is a graphical illustration of an eco-industrial park time zonesstreams data map according to an embodiment of the present invention.

FIG. 38 is a graphical illustration of an energy consumption calculationwebpage form illustrating eco-industrial park intra-time zone energytargeting (Zone 1) according to an embodiment of the present invention.

FIG. 39 is a graphical illustration of an energy consumption calculationwebpage form illustrating eco-industrial park intra-time zone energytargeting (Zone 2) according to an embodiment of the present invention.

FIG. 40 is a graphical illustration of an energy consumption calculationwebpage form illustrating eco-industrial park intra-time zone energytargeting (Zone 3) according to an embodiment of the present invention.

FIG. 41 is a graphical illustration of an energy consumption calculationwebpage form illustrating eco-industrial park intra-time zone energytargeting (Zone 4) according to an embodiment of the present invention.

FIG. 42 is a graphical illustration of an energy consumption calculationwebpage form illustrating eco-industrial park intra-time zone energytargeting (Zone 5) according to an embodiment of the present invention.

FIG. 43 is a graphical illustration of an energy consumption calculationwebpage form illustrating eco-industrial park inter-time zones targetingcalculations according to an embodiment of the present invention.

FIG. 44 is a graphical illustration of an eco-industrial park bestcoupling between two time zones according to an embodiment of thepresent invention.

FIG. 45 is a graphical illustration of an eco-industrial park secondbest coupling between two time zones according to an embodiment of thepresent invention.

FIG. 46 is a graphical illustration of an eco-industrial park best twocouplings between two time zones according to an embodiment of thepresent invention.

FIG. 47 is a graphical illustration of an eco-industrial park secondbest two couplings between two time zones according to an embodiment ofthe present invention.

FIG. 48 is a graphical illustration of an eco-industrial park bestintegration between three time zones according to an embodiment of thepresent invention.

FIG. 49 is a graphical illustration of an eco-industrial park secondbest integration between three time zones according to an embodiment ofthe present invention.

FIG. 50 is a graphical illustration of an eco-industrial park bestintegration between four time zones according to an embodiment of thepresent invention.

FIG. 51 is a graphical illustration of an eco-industrial park secondbest integration between four time zones according to an embodiment ofthe present invention.

FIG. 52 is a graphical illustration of a temperature time duty diagramfor inter-time zones (temporal) integration solutions finding accordingto an embodiment of the present invention.

FIG. 53 is a graphical illustration of a temperature time duty diagramillustrating an option for inter-time zones matching according to anembodiment of the present invention.

FIG. 54 is a graphical illustration of a temperature time duty diagramillustrating an option for inter-time zones matching according to anembodiment of the present invention.

FIG. 55 is a graphical illustration of a temperature time duty diagramillustrating an option for inter-time zones matching according to anembodiment of the present invention.

FIG. 56 is a graphical illustration of a temperature time duty diagramillustrating an option for inter-time zones matching according to anembodiment of the present invention.

FIG. 57 is a graphical illustration of a temperature duty diagram forinter-processes (spatial) integration in time zone t1 example accordingto an embodiment of the present invention.

FIG. 58 is a graphical illustration of a temperature duty diagramillustrating all possible options for inter-processes (spatial) matchingabove pinch according to an embodiment of the present invention.

FIG. 59 is a graphical illustration of a temperature duty diagram(option 1) for inter-processes (spatial) integration in time zone t1according to an embodiment of the present invention.

FIG. 60 is a graphical illustration of a temperature duty diagram(option 2) for inter-processes (spatial) integration in time zone t1according to an embodiment of the present invention.

FIG. 61 is a graphical illustration of a temperature duty diagram(option 3) for inter-processes (spatial) integration in time zone t1according to an embodiment of the present invention.

FIG. 62 is a graphical illustration of a temperature duty diagram(option 4) for inter-processes (spatial) integration in time zone t1according to an embodiment of the present invention.

FIG. 63 is a block flow diagram illustrating a process of determiningthe sizes and number of major units of a utilities combined heat andpower complex at their respective locations according to an embodimentof the present invention.

FIG. 64 is a graphical illustration of an exemplary industrial citytotal steam demand table according to an embodiment of the presentinvention.

FIG. 65 is a graphical illustration of an exemplary industrial citytotal power demand table according to an embodiment of the presentinvention.

FIG. 66 is a graphical illustration of an equipment name and operatingcapability input form according to an embodiment of the presentinvention.

FIG. 67 is a graphical illustration of a steam header definition inputform according to an embodiment of the present invention.

FIG. 68 is a graphical illustration of a motor and steam turbine datainput form according to an embodiment of the present invention.

FIG. 69 is a graphical illustration of a set of combined heat and powdermodel input data entry forms/fields according to an embodiment of thepresent invention.

DETAILED DESCRIPTION

The present invention will now be described more fully hereinafter withreference to the accompanying drawings, which illustrate embodiments ofthe invention. This invention may, however, be embodied in manydifferent forms and should not be construed as limited to theillustrated embodiments set forth herein. Rather, these embodiments areprovided so that this disclosure will be thorough and complete, and willfully convey the scope of the invention to those skilled in the art.Like numbers refer to like elements throughout. Prime notation, if used,indicates similar elements in alternative embodiments.

System Structure:

An Eco-Industrial Park (EIP) can include an industrial city or citiesand the non-industrial community. An industrial city or site typicallycontains a number of zones. Each zone contains blocks, e.g., east, west,north and south. Each block contains a number of facilities, e.g., oilrefinery; plastics complex, pulp & paper, etc. Each facility (e.g., anoil refinery) contains a number of time-dependent and non-dependentplants, e.g., a hydrocracking plant, naphtha hydrotreating plant (NHT),crude distillation plant, etc. Each plant (e.g., an NHT plant) containsa number of units, e.g., a stripping unit, naphtha splitting unit,reaction unit, etc. Each unit contains a number of hot process streamsthat need to be cooled and cold process streams that need to be heated,e.g., feed stream to the naphtha splitter, bottom product stream, topproduct stream, feed stream to reboiler, feed stream to condenser, etc.The nonindustrial community can include malls, hospitals, hotels,housing compounds, schools and so on. In eco-industrial parks, there arenumerous industrial and non-industrial activities distributed over spacein the form of cities' zones/blocks/facilities/processes, and over timein the form of batch, semi-batch and continuous combinations. For energyintegration among eco-industrial parks members, there can be a verysubstantial number of combinations at multiple time zones. For example,for a 25 plant industrial activity, there can be up to 4.6386×10¹⁸integration combinations for just one time zone. Various exemplarysystem options according to a plurality of exemplary embodiments of thepresent invention are described below.

FIG. 1 illustrates an eco-industrial park containing any number ofadjacent industrial facilities, batch, semi-batch, and continuousindustrial process facilities, and non-industrial communities includingresidential and community houses labeled as 1, commercial buildings,hospitals, churches, mosques, etc. labeled as 2, and industrial plantslabeled as 3, 4, 5, 6, 7, 8, 9, and 10.

FIG. 2 illustrates a system/apparatus 30 to target for enhanced energyefficiency for an eco-industrial park through identifying hybrid directand indirect inter-systems-inter-time-zones matching solutions throughselecting best energy efficient routes; generating technically viableenergy efficient eco-industrial parks alternatives, identifying bestgeneration and allocation of energy utilities, and synthesizing thecombined heat and power utility system that satisfies the eco-parkdemands during each time zone as well as rendering its best operatingscenario at each specific time-zone to provide enhanced energyefficiency and reduced greenhouse gas emissions for a mega industrialsite. This inter-systems-inter-time-zones integration can includeidentifying the best and the second best matching(s) solutions amongprocesses in the eco-industrial park for spatial energy integration andthe best and second best matching(s) solutions among all time-zones fortemporal energy integration and GHG emissions reduction for the optimalsynthesis or retrofit of eco-industrial parks, using all possiblecombinations of processes-specific design and operations modifications.

The system 30 can include an inter-time zones inter-systems integrationanalysis and design computer 31 having a processor 33, memory 35 coupledto the processor 33 to store software and database records therein, anda user interface 37 which can include a graphical display 39 fordisplaying graphical images, and a user input device 41 as known tothose skilled in the art, to provide a user access to manipulate thesoftware and database records. Note, the computer 31 can be in the formof a personal computer or in the form of a server or server farm servingmultiple user interfaces 37 or other configuration known to thoseskilled in the art. Accordingly, the user interface 37 can be eitherdirectly connected to the computer 31 or through a network 38 as knownto those skilled in the art.

The system 30 can also include one or more databases 43 stored in thememory 35 (internal or external) contained within, associated with orcoupled to the inter-time zones inter-systems integration analysis anddesign computer 31 and having various forms of eco-industrial park megasite data to include: a plurality of sets of values each separatelydefining operational attributes for each of a plurality of hot processstreams and a plurality of cold process streams. Such attributes caninclude, for example, a value for supply temperature (Ts) of each of thehot process streams and each of the cold process streams, a value for atarget temperature (Tt) of each of the hot process streams and each ofthe cold process streams, and/or a value for a heat capacity flow rate(FCp) of each of the hot process streams and each of the cold processstreams.

The one or more databases 43 can also include one or more sets ofstream-specific minimum temperature approach values between streams(ΔT_mini, j, k, l, m), streams initial types, streams matchingconstraints, global utility consumption values Qh, Qc for the entirepark to a consumption varies for each time zone, utility consumptionvalues for each spatial zone, system surplus and deficit values aboveand below the pinch point, as well as the interval and/or discretelocations of the pinch regions often referred to as a “pinch point,”which describe a “region of minimum choice lower and upper temperatureboundaries” when in interval form, at least for each pinch pointcontrolling process stream temperature. The one or more databases 43 canalso include identification of the streams, processes, units,facilities, plants, and/or zones that control the pinch locations, datalinking the pinch points to define a map or maps of the pinch locationsaccording to a progressive change in ΔT_min_i or process conditions, andthe minimum number of heat exchanger units required for a networkcondition at each pinch. The one or more databases 43 can also includesuch data for one or more hot oil circuits and buffer systems, and caninclude capital costs of various heat exchangers network and bufferequipment and hot oil circuit equipment for the industrial site.

The one or more databases 43 can further include fuel type/energy source(coal, heavy fuel oil, natural gas, biomass, waste materials, solaretc.), equipment which generate steam (for heating purposes, pumps andcompressors driving, heat carrying, cleaning, cooling) and power (forlighting and other applications), steam headers and its range ofconditions (pressure or saturation temperature), shaft work networkconfiguration, and the range of values with respect to allocation ofsteam and power to both process and utility plants usage, and discretevalues identified as providing optimal and potentially optimal results,among others as would be understood by those of ordinary skill in theart.

The one or more databases can also include an identification of best andsecond best. The one or more databases 43 can also include the topologyof the mega industrial site and final direct and indirect connectionpoints, steam headers, and oil circuits.

The system 30 can also include an inter-time zones inter-systemsintegration analysis and design program 51 stored in memory 35 of theinter-time zones inter-systems integration analysis and design computer31 and adapted to provide systematic processes that include variousunique phases of analysis and design. The unique phases of analysis anddesign can beneficially provide a revolutionary solution approach toprovide systematic methods/tools that enable the designer to firsttemporarily target for inter-time zones integration prior to targetingfor intra-time zone integration. Additionally, the designer canbeneficially first spatially target for direct and indirect loads forintegration, without leaving anything “on the table” and generate asmany technically viable options/alternatives/solutions as necessary toattain desired level of energy consumption.

FIG. 3 illustrates the interconnection between the majorprocesses/program modules according to an exemplary embodiment of thepresent invention. The program 51 can incorporate one or morecombinations of the following processes/program modules: atime-dependent processes inter-time zones energy integration and initialsolution finding module 52, a domino-effect steam sharing module 53, aneco-industrial parks membership management module 54, an energyintegration via temporal and spatial systems matching module 55, and amulti-time period eco-park utility system synthesis and operationplanning model module 56. The program 51 can also includeprocesses/program modules 61, which provide system-wide global energytargeting under all possible combinations of standalone in-processmodifications and stream-specific minimum approach temperatures. One ormore of the processes/program modules 61 receive mega site input data 62including internal or interface structural connections and operationalattributes for adjacent cities, industrial site zones, blocks,facilities, plants, units, and streams. These processes/program modules61 include, but are not limited to, those described in thepatents/patent applications listed in Appendix 1. The program 51 canalso include: an optimal energy systems consumption combinations testprogram module 63, a number-of-steam headers' and conditions' impact onenergy consumption test program module 64, a realizable energy targetsusing direct or indirect integration test program module 65, aninter-system thermal loads sharing calculation program module 66, adirect inter-systems energy integration solution finding program module67, a hybrid inter-systems energy integration solution finding programmodule 68, and synthesis of central multi-generation utilities systemprogram module 69, which can provide for synergy with the industrialcommunity.

Note, the inter-time zones inter-systems integration analysis and designprogram 51 can be in the form of microcode, programs, routines, andsymbolic languages that provide a specific set for sets of orderedoperations that control the functioning of the hardware and direct itsoperation, as known and understood by those skilled in the art. Notealso, the inter-time zones inter-systems integration analysis and designprogram 51, according to an embodiment of the present invention, neednot reside in its entirety in volatile memory, but can be selectivelyloaded, as necessary, according to various methodologies as known andunderstood by those skilled in the art.

Methodology Overview

In eco-industrial parks, there are numerous industrial andnon-industrial activities distributed over space in the form of cities'zones/blocks/facilities/processes, and over time in the form of batch,semi-batch and continuous combinations. Various embodiments of theinvention can provide a huge potential for energy consumption and GHGemissions reduction attainable through smart energy integration amongseveral industrial and non-industrial processes and activities ineco-industrial parks.

Various embodiments provide systems, computer readable media, programproducts/code, and methods that can find in the planning of a neweco-industrial park, or its transition from just an industrial complexto an eco-city: the best time (temporal) and space (spatial) zonesmatching, the best blocks matching, best facilities matching, and thebest streams matching that achieves the best energy saving and GHGemissions reduction. An approach adopted according to one or moreembodiments of the present invention incorporates a hybrid methodologythat systematically looks to all options together to find the bestcombinations out of the available solutions package.

According to one or more embodiments, the matching can be implementeddirectly and/or indirectly. Directly matching can be accomplished byfinding the best matching without any buffers. Indirect matching can beaccomplished by utilizing water, steam, hot oil, all of them, or acombination thereof. A zone, a block, a facility and finally a processstream can be utilized as a buffer or as an ambassador to take energyfrom one place and transfer it to another. The matching can be performedusing advanced matching techniques where a zone, a block or a facilityor a stream can match homogeneously and/or heterogeneously. The advancedmatching techniques can also include those where a zone, a block or afacility or a stream can be manipulated to change its identity fromenergy supplier to energy receiver and return back to energy supplier orfrom energy receiver to energy supplier and return back to energyreceiver.

Beneficially, the matching can also be performed under all possiblecombinations of process changes in each facility in a way that perfectsthe matching of a facility with other facilities in the same blockand/or with other blocks and/or matching within the same zone and/orwith other zones using direct, indirect, and hybrid methods ofintegration. Beneficially, the matching can be accomplished at each timezone via intra-time energy integration, and/or through reasonablypossible inter-time-zones integration using: energy storage, industrialand non-industrial processes and activities rescheduling, as well asthroughput/durations schedules optimization, or all of the above.

Matching of streams can be accomplished, for example, throughapplication of the latest advanced matching techniques depicted in U.S.Pat. No. 7,729,809, titled “System, Method, and Program Product forTargeting and Identification of Optimal Process Variables in ConstrainedEnergy Recovery Systems,” U.S. Pat. No. 8,116,920, titled “System,Method, and Program Product for Synthesizing Non-ThermodynamicallyConstrained Heat Exchanger Networks,” U.S. patent application Ser. No.12/767,315, filed Apr. 26, 2010, titled “System, Method, and ProgramProduct for Synthesizing Heat Exchanger Networks and Identifying OptimalTopology for Future Retrofit,” and U.S. Pat. No. 8,032,262, titled“System, Method, and Program Product for Synthesizing Non-Constrainedand Constrained Heat Exchanger Networks.” The hot and cold processstreams can be matched intra-process and inter-process in both a singletime zone and across multiple other times, and/or the hot and coldstreams of each zone, block or facility can be consolidated into asingle representative process stream and cold process stream and matchedhomogeneously and/or heterogeneously.

The advanced matching can allow for a zone, a block or a facility or astream to change its identity from energy supplier to energy receiverand return back to energy supplier or from energy receiver to energysupplier and return back to energy receiver. The advanced matching canalso be performed under all possible combinations of reasonablyanticipated process changes in each facility, for example, in a way thatperfects the matching of the respective facility with other facilitiesin the same block and/or with other blocks and/or within the same zoneand/or with other zones using direct, indirect and hybrid methods ofintegration.

This can also be accomplished, for example, under a set ofstream-specific minimum approach temperatures (ΔT_min_i, j, k, l, m)which provide an optimal combination for enhanced energy recovery, where“i” refers to the hot stream number, “j” refers to process number, “k”refers to plant/facility number (industrial or non-industrial) and “l”refers to block number and “m” refers to the zone number. Alternatively,the stream-specific minimum approach temperatures (ΔT_min_i, j, k₁, k₂,l, m) are further identified by the stream location within the plantwithin the facility, where “k₁” refers to the plant number, and “k₂”refers to the facility number. U.S. Pat. No. 7,873,443 “System, Method,and Program Product for Targeting and Optimal Driving Force Distributionin Energy Recovery Systems,” incorporated herein by reference, describesa methodology of calculating a set of stream-specific minimum approachtemperatures for a process. According to this exemplary configuration,for application to a mega industrial city, the algorithm includesadditional stream identification to include the process, plant,facility, block, and/or zone number. The targeting module according tothe exemplary configuration can define upon the energy targetscalculation which stream(s), unit, plant, facility, block and zonecontrols the pinch location for the whole problem under the currentminimum approach temperature and for future ones.

The analysis can beneficially be performed to identify the best possiblescenarios for inter-time zones inter-processes/systems integration andthe most cost effective solution(s) now and in the future at thetargeting phase via “plants' smart matching.” The exemplaryconfiguration provides a systematic methodology/technique to first dothe right integration at the highest level and then to do the rightintegration at the lower levels. The right integration at the highestlevel includes the identifying of what load to integrate and among whatsystems to do so, along with the identifying of the possible matches andloads to consider and others to neglect (e.g., small energy values). Theright integration at the lower levels includes identifying the optimalmethod of inter-systems integration, i.e., direct, indirect or hybrid,and if indirect or hybrid, identifying it's medium, i.e., water, steamor hot oil, and performing smart matching or combinations.

Conventional methods can result in a twofold loss in energy. The firstis energy loss in form of quality due to the “without pockets thermalheat” intra-plant integration, which is not included in the inter-plantsintegration; and the second is due to the lumping of different steamgeneration and/or demand levels. The first form of energy quality lossresults, for example, from performing intra-process integration firstfollowed by the inter-processes integration. In most of the cases, thisresults in matches between hot streams and cold streams with approachtemperatures much higher than the recommended minimum, which can resultin thermal energy degradation that could otherwise be used to satisfyother processes or generate work when other lower grade energy inanother process could be used to satisfy the need of the first process.The second form of energy loss is due to the way steam from waste hotprocess streams is generated. For example, if steam is generated atcertain temperature in process “A,” in order to use it in anotherprocess “B” its temperature must be higher than the process needs, whichin many cases is not possible.

Various embodiments of the invention provide solution alternatives thatinclude best utility synthesis and/or best utility system operatingscenario for each time interval. According to an embodiment, the utilitysystem synthesis identifies the whole eco-industrial park power andsteam generation structure, number of units (combustion gas turbines,steam turbines, solar systems, diesel, heat recovery steam generators,and so on), equipment sizes and capacities to generate both heat andpower which satisfy the eco-industrial park’ needs for both power andheat at any time. According to an embodiment, the utility systemoperating scenario provides the number of equipment and capacitiesrunning at each time period of operation in summer, winter, partialloads, peak loads and so on.

Conventional methods do not include the analysis and selection of thedifference between the stream supply and target pressure of hot streamsto be cooled or cold streams to be heated as degrees of freedom, i.e.,using the difference as an optimization variable to create extra heatingor cooling capabilities. Various embodiments of the invention performsuch analysis and selection process. Many streams have high pressure tobe reduced and low pressure to be increased. Reducing the streampressure results in a reduction in the supply temperature of such streamwhich translates to a cooling capacity. The increase in pressure ofother streams results in an increase of its supply temperature and itscapacity for heating. Such variables can be optimized for the sake ofthe whole inter-process integration. According to an embodiment, theenergy targeting module uses intervals for the supply temperaturesand/or target temperatures of the streams. The supply temperatureinterval can represent the possible pressure increase of a stream orpossible pressure reduction of another to achieve optimum energyconsumption saving of the whole eco-industrial park. As such, one ofordinary skill in the art will understand that optimized steam pressurecan be extracted from the optimization problem through optimization ofthe supply temperature provided a relation is established or understoodto exist between steam pressure and the supply temperature.

Conventional methods prevent indirect inter-plants integration usingsteam because of the long distances involved due to capital costrequirements, and/or condensation problems. Various embodiments of theinvention advantageously utilize a “Beyond-Cooperation” approach througha “Domino-Effect-Steam-Transfer/Steam-Propagation/Steam Sharing Module”in which processes of a plant act as ambassador to a pair of plants: onesupplying steam and one requiring steam. Various embodiments canidentify such ambassadors. For example, Plant A's hot streams cangenerate steam. Instead of integrating such hot streams with the plantcold streams, Plant A transfers steam to Plant B, which does not needsteam. Plant B will then be able to generate steam to give it to nextdoor Plant C, avoiding the long distance between Plants A and C.

Conventional methods use waste heat in form of hot process streams orwaste steam to offset an adjacent plant's thermal heat deficit. Variousembodiments of the present invention systematically include wastecooling capacities for integration as well. Further or alternatively,various embodiments provide steps/operations for simultaneously spatialand temporal inter-systems integration which enhance load smoothing orpeak-lopping due to high intermittent loads on heat and/or power.

Additionally, various embodiments of the invention provide a methodologyfor inter-time-zone integration that is rigorous as compared to the twofamous state-of-the-art methods: the time pinch method and cascadealgorithm, described by Ian C. Kemp, “Pinch Analysis and ProcessIntegration” p. 271 (2007), which are not rigorous and thus, do notprovide a consistently accurate solution. For example, the energytargets calculated using one or more embodiments of invention, appliedto the primitive example illustrated in FIGS. 13-14, renders Q_heating=0units and Q_cooling=0 units. In contrast, as shown in FIGS. 16-17, theconventional methodologies on the same primitive example would renderhigher energy targets, on the order of Q_heating=200 units andQ_cooling=200 units, which means that they do not provide the optimalsolution, or even a sufficient solution. Consequently, the conventionalsystems can cause the user to miss out on numerous possible solutions inthe solutions' space for energy saving otherwise available if theyemployed inter-time-zones energy integration according to variousembodiments of the invention.

There are several reasons behind their erroneous energy targetscalculation. For example, the cascade analysis method limits thepotential scope of its inter-time zones energy integration by firstconducting an intra-time zone integration in a first time zone (“t1”),and then if there is surplus energy below the pinch temperature in thefirst time zone t1, it is transferred to next time zone (“t2”) above itspinch for inter-time zones energy integration. In such scenario, themethod used will be expected to miss numerous opportunities due to themishandling of the temperature/thermodynamic constraint. For example,according to the cascade methodology, a hot stream carrying waste heatat a certain temperature in time zone t1 can only transfer heat to timezone t2, i.e., the next time zone as per the cascade method, if and onlyif its temperature is higher than that of the cold stream in time zonet2 by a minimum temperature difference or more. Otherwise if there is nocold stream in time zone t2, having such criterion then the waste heatin the hot stream in time zone t1 will be wasted to a cooling media.

Also for example, the energy targeting method, in its calculation logicand procedures, treats the time constraint as a hard constraint. Anexample includes treating the range/length of the boundaries/time zoneintervals as hard constraints. Another example happens when the hotstream to be cooled exists in a later time zone while the cold stream tobe heated exists in an earlier one. This limitation deprives it frombeing inclusive, resulting in the loss/missing of numerous possibleopportunities, even though the time constraint can be relaxed/overcomethrough use of various process solutions such as, for example,rescheduling of streams, storage of a hot stream to next batch, using ofa buffer stream, using an in-process waste utility stream, storing acold stream to future time zones, using advanced matching techniques asin the cases of non-thermodynamic constraints, as well as manipulatingstreams flow rates across the time zones (e.g., increase, decrease andboth).

A buffer stream such as water, hot oil and so on or in-processcondensate stream, waste water stream or steam condensate stream and soon can be used, for example, to take the thermal load available heatingor cooling and transfer it to another plant in another time zone. Forexample, the stream can take the thermal load from a hot stream orstreams that need to be cooled in time zone t1 without interrupting anassociated batch process path, and use it to give heat to a cold streamin time zone t2. In order not to delay the batch process in time zonet1, a storage tank can be used for the hot stream. Using advancedmatching techniques can be conducted, for example, via allowing a secondhot stream “H2” leaving time zone t1 to time zone t2 for furtherprocessing to be heated up by a first hot stream “H1” in time zone t1.H2 receives extra heating load while cooling down H1 to continue itsprocessing path in time zone t1. The extra heating load added to the H2stream already embarked for processing time zone t2 can then betransferred to cold streams to be heated in time zone t2. The H2 stream,in such case, is a thermal heating load “carrier” that receives heatfrom one zone to be used in another time zone into which it is alreadyheading for further processing.

Experts in the field have recognized a long felt need for a targetingmethodology that identifies the maximum potential for heat recovery. Theexperts will also recognize the benefits of the methodology of doing soaccording to various embodiments of the invention, which can includetaking time constraints, thermodynamic/temperature constraints, andnon-thermodynamic constraints (e.g., forbidden heat transfer/matching)into consideration simultaneously, and not sequentially. Experts in thefield will also understand that the calculated attainable global maximumpotential for heat recovery provided according to one or moreembodiments of the invention, can be waived, typically at the managementlevel, later on in favor of allowing for higher utility energyconsumption targets as determined according to various solutions'options, based upon “big picture” economics and/or process objectives'priorities.

Various embodiments of the invention provide a problem representationfor targeting and solutions generation using a time and temperature dutydiagram (TTDD) or T2D2 graph. Various embodiments of the inventionprovide hybrid integration in time and space simultaneously. Variousintegration scenarios include energy storage and transfer and/orprocess-specific rescheduling in the context of the overall system forinter-time and/or inter-space integration. One or more embodiments,industrial and non-industrial systems in the problem representationboundary. One or more embodiments provide targeting for the bestcandidate and the second alternative and so on for eco-park membershipfor any number of zones, blocks, facilities, plants processes andstreams as well as any number of time intervals. According to one ormore embodiments, solution alternatives include multiple alternativesfor economic evaluation to include: process-specific conditionsmodifications, rescheduling, energy storage, and processes matching toinclude batch-with-batch and batch-with-continuous, among others asunderstood by those of ordinary skill, in both time and space. Solutionalternatives can include best utility synthesis and best utilityoperating scenario for each time interval in the eco-industrial park.Various embodiments also include a methodology for designing candidatesolutions with retrofit in mind or retrofit with further retrofit inmind, hybrid indirect medium integration solutions, simultaneousconsideration of utility and processes design or retrofit, andprocess-specific structural and operations changes (e.g., temperaturesand pressure), as well as stream-specific minimum approach temperature.

Multi-Process Approach

The various embodiments of the present invention beneficially providenew tools for the mega-problem representation, targeting forinter-processes energy integration, and processes/plants matching. FIG.4 illustrates synthesis of a central multi-generation utilities systemin synergy with an industrial community and a non-industrial community.As an example, at least partially shown in FIG. 4 is an exemplarycombined heat and power modified structure interfaced with residentialhousing labeled as 1, commercial building, hospitals, churches, mosques,etc. labeled as 2, and other industry site zones 3-10 shown in FIG. 1.

According to an embodiment, the tools for solving the mega-problem forthe eco-industrial park shown, e.g., in FIG. 4 include multipleprocesses/procedures including but not limited to: performingeco-industrial parks inter-time zones inter-systems energy integrationto using, for example, the time-dependent processes inter-time zonesenergy integration and initial solution finding module/method 52 (FIGS.3 and 10-14), performing hybrid inter-time inter-system matching; andperforming eco-industrial park membership management utilizing, forexample, eco-industrial park mathematical program model 54 (FIGS. 3 and18). The processes/procedures can also include: performing adomino-effect model for low pressure steam targeting process using, forexample, the domino-affect steam sharing module/method 53 (FIGS. 3, 19,and 24); performing a multi-levels multi-facilities steam targetingprocess (FIGS. 25-27); and data extraction and utility energy targeting(FIGS. 28-34). FIGS. 35-51 provide targeting and best coupling examples.The processes/procedures can further include energy integration viatemporal and spatial systems matching using module/method 55 (FIGS.52-62), and developing multi-time period combined heat and power modelsfor eco-industrial park utility system synthesis and planning underuncertainty utilizing, for example, the multi-time period eco-industrialpark utility system synthesis and operation planning models 56 (FIGS.3-5 and 63-69).

In performing these processes/procedures, the following issues areaddressed systematically: inter-time zones inter-systems energyintegration; hybrid inter-time inter-systems matching; low pressuresteam targeting utilizing a domino effect model;multi-levels-multi-facilities steam targeting; mathematical programmodeling for eco-industrial park membership management; best and secondbest couplings of temporal zones inter-zones/systems integration;multi-time period combined heat and power modeling; and energyintegration via temporal and spatial systems matching, each potentiallyperformed under all possible combinations of process-specific designmodifications and advanced matching. Additional issues also oralternatively include, but are not limited to: spatial direct andindirect as well as hybrid integration (i.e., when to use direct,indirect or both); addressing partial and totally forbidden matches;best and second best couplings of spatial zones, facilities, units andstreams using direct integration for any number of industrialfacilities; targeting and finding solutions; and design or retrofit withfuture retrofit-in-mind, addressed in detail in U.S. patent applicationSer. No. 13/858,731 and U.S. patent application Ser. No. 13/858,718, therelated discussions of which are incorporated by reference in theirentirety.

According to an exemplary configuration, using the composite curvesbuilding method, all streams for all time periods/zones can berepresented in one temperature interval graph, problem-wide pinchpoint(s) can be defined and an optimal pinch temperature can beidentified. Additionally, the zone; block, facility, process unit andstream controlling pinch point location(s), both spatially andtemporally, can be found. Further, the zone(s); block(s), facility(s),process unit(s), and stream(s) and time zones having a high and highestimpact on the waste energy recovery problem can be located. A graphicaltechnique can also be used to identify the minimum direct number ofmatches/connections among zones or blocks or facilities or processes(U.S. patent application Ser. No. 13/858,731 and U.S. patent applicationSer. No. 13/858,718), spatially and/or temporally. A graphical techniquecan also be used via the all-in-one composite lines to decide theamounts of indirect heating and indirect cooling duties and itsassociated temperature levels above and below the problem-wide pinch, aswell as the estimated targets for extractable work above the pinch andreducible work below the pinch. Note, in cases where the pinchtemperature is equal to ambient temperature or below, according to anembodiment, one can expect only extractable work above the pinch andreducible work below the pinch. In all of the cases, according to anembodiment, one can expect to find and can identify extractable workabove and below the pinch.

Prior to providing an eco-industrial park problem wide representation,the following discussions regarding eco-industrial park inter-time zonesinter-systems energy integration, methods of constructing a newlydeveloped problem-wide time-temperature duty diagram (T2D2), and hybridinter-time inter-systems matching procedures, are provided.

Eco-Industrial Parks Inter-Time-Zones-Inter-Systems Energy IntegrationModule:

The eco-industrial park inter-time zones inter-systems energyintegration module/process, described with respect to FIG. 6, caninclude the following steps:

Step 1 Extract all the heating and cooling tasks for all significantindustrial and non- industrial activities in/for the whole of the entireeco-industrial park. Step 2 Construct a time-space schematic for theeco-industrial park heating and cooling tasks to identify the time zonesboundaries. Step 3 Use the Time-Temperature-Duty-Diagram to establish asupply (s)-demand (d)- cascade from heating and cooling tasks,respectively at each temperature interval. Step 4 Use step # 3 tocalculate (a) “S” supply and “D” demand at each temperature interval viacascading “s” and “d” in time and (b) inter-time zones energy loadstorage and/or rescheduling requirements (“st11”, “st12”, “st21”,“st31”and so on) among time zones for the whole eco-industrial park.Step 5 Use step # 4 to calculate via another cascade in “S” and “D,” theglobal minimum heating and cooling needs of the whole eco-industrialpark's time-dependent and non-dependent industrial and non-industrialactivities. Step 6 For eco-industrial park heating and cooling needs,uncertainties inclusion in the calculation steps from #1 to #2 will beconducted using intervals instead of real numbers.

Step 1 includes extracting all the heating and cooling tasks for allsignificant industrial and non-industrial activities in/for the entireeco-industrial park. This can be accomplished via entering input data inan input table or spreadsheet, such as, for example, Table 1 shown belowfor a single batch process, or in an input webpage form similar to thatshown in FIG. 29.

TABLE 1 Time Zone Duration(hour) Stream type Ts Tt FCpt t1 0-1 H1 400300 2 t2 1-2 C1 0 100 2 t3 2-3 C2 280 380 2 t3 2-3 H2 120 20 2

Step 2 includes constructing a time-space schematic for theeco-industrial park heating and cooling tasks to identify the time zonesboundaries. According to the exemplary configuration, the time zoneboundaries are defined by the smallest heating or cooling time durationof any activity in the park under analysis. According to a lessdesirable alternative, the smallest time zone can be a standard timeblock such as, 1 hour, one minute, other, or a combination standard andactivity specific thereof.

Step 3 includes establishing a supply (s)-demand (d) cascade fromheating and cooling tasks, respectively, at each temperature interval(T1-Tm), using, for example, a Time-Temperature-Duty-Diagram (T2D2),described below. FIG. 6 illustrates an exemplary model illustrating thesupply-demand cascade.

Step 4 includes: (a) calculating the energy supply S1-Sm and the demand(D1-Dm) at each temperature interval (T1-Tm) via cascading supply “s”and demand “d” in each separate time zone, and (b) calculatinginter-time zones energy load storage and or rescheduling requirements(“ST11”, “ST12”, “ST21”, “ST31” and so on) among time zones (t1-tn) forthe whole eco-industrial park. Note, ST11 represents storage attemperature interval T1 and time zone t1.

Step 5 includes calculating the global minimum heating (Qh) and globalminimum cooling (Qc) needs of the whole of the eco-industrial parktime-dependent and non-dependent industrial and non-industrialactivities via another cascade in “S” and “D.” Note, in the special caseof a threshold problem requiring only heating utility or coolingutility, the global value can be calculated by summing the respectiveD1-Dm or S1-Sm.

Step 6 includes including intervals instead of real numbers in thecalculations performed in steps 1-5 where it is desired to includeuncertainties in the eco-industrial park heating and cooling needs.

Method for Constructing Problem-Wide Time-Temperature-Duty Diagram(T2D2):

The eco-industrial park inter-time zones inter-systems energyintegration module/process, described with respect to FIGS. 7-9 and 13,can include the following steps:

Step 1 Define the problem time and space zones, blocks, facilities,plants and processes considered for inter-systems energy integration.Step 2 Construct the global Cold Composite Line (gCCL) for all thezones, blocks, facilities, plants and processes' streams in each timezone. Step 3 Construct the global Hot Composite Line (gHCL) for all thezones, blocks, facilities, plants and processes' streams in each timezone, with embedded ΔT_min for specific zone, block, facility, plant,process and stream and steam headers as well as hot oil circuits. Step 4Locate the problem-wide desired pinch and the pinch-location controllingprocess/stream. Step 5 Draw the global Cold Composite Line (gCCL) foreach time zone above and below the pinch. Step 6 Draw the global HotComposite Lines (gHCL) for each time zone above and below the pinch.Step 7 Write the thermal load on the top of each time zone above thepinch. Step 8 Write the thermal load on the bottom of each time zonebelow the pinch. Step 9 Write the Surplus Heating Load for each timezone at the top left corner above the pinch and bottom left corner belowthe pinch (include Qc). Step 10 Write the Deficit Heating Load for eachtime zone on the bottom right corner below the pinch and on the topright corner above the pinch (include Qh).

Note, U.S. patent application Ser. No. 13/858,731 and U.S. patentapplication Ser. No. 13/858,718, provides a detailed discussionregarding obtaining data, constructing global hot and cold compositelines, identifying problem wide pinch locations and pinch controllingprocesses/zones/streams.

Step 1 includes defining the problem time and space zones, blocks,facilities, plants and processes considered for inter-systems energyintegration. This can include identifying the spatial structure and timedurations of batch, semi-batch, and continuous activities/facilities,for example.

Step 2 includes constructing the gCCL for all the zones, blocks,facilities, plants and processes' streams in each time zone (t1-t3 inthis example).

Step 3 includes constructing the gHCL for all the zones, blocks,facilities, plants and processes' streams in each time zone, withembedded ΔT_min for specific zone, block, facility, plant, process andstream and steam headers as well as hot oil circuits. Note, the steamheaders and hot oil circuits exchangers are assigned one-half theminimum approach temperature of each hot stream they receive load from.

Step 4 includes locating the problem-wide desired pinch and thepinch-location controlling process/stream. The pinch controlling streamis one of the streams extending from the problem-wide desired pinch andcan be identified by changing values of the suspect stream or streams tosee if the problem wide pinch location changes.

Step 5 includes drawing the gCCL for each time zone (t1-t3) above andbelow the pinch, and Step 6 includes drawing the gHCL for each time zone(t1-t3) above and below the pinch. FIG. 7 illustrates developing a timeinterval graph that can be used for identifying the hot streams “H” andcold streams “C” for each of the various processes/zones, etc. for eachtime zone. FIG. 8 illustrates a time duty diagram (TDD) whichgraphically provides the global hot and cold composite lines for eachspatial designation (e.g., zone, process, etc.) labeled as “Q1-Q3” inthe figure for each time zone labeled “t1-t3” in the figure. FIG. 9illustrates a temperature-time duty-diagram which graphically displaysthe hot and cold composite lines for each time zone for each temperatureinterval.

Step 7 includes writing/transferring the thermal load on the top of eachtime zone (t1-t3) above the pinch (see, e.g. FIG. 9), and Step 8includes writing the thermal load on the bottom of each time zone(t1-t3) below the pinch.

Step 9 includes writing/transferring the Surplus Heating Load for eachtime zone at the top left corner above the pinch (see, e.g., FIG. 13)and bottom left corner below the pinch, along with the value of globalcooling utility requirement value Qc, and Step 10 correspondinglyincludes writing/transferring the Deficit Heating Load for each timezone on the bottom right corner below the pinch and on the top rightcorner above the pinch, along with global heating utility requirementvalue Qh.

Note, the Surplus Heating Load above the pinch is the load that needs tobe recovered via inter-time-zones-inter-systems energy integration,otherwise cooling duty above the eco-industrial park problem pinch willbe required, which results in a loss in energy efficiency. The SurplusHeating Load below the pinch is the load that needs to be recovered viainter-time-zones-inter-systems energy integration, otherwise morecooling duty will be needed above desired energy target. The DeficitHeating Load below the pinch is the load that needs to be provided viainter-time-zones-inter-systems energy integration, otherwise heatingduty below the eco-industrial park problem pinch will be required, whichresults in loss in energy efficiency. The Deficit Heating Load above thepinch is the load that needs to be provided viainter-time-zones-inter-systems energy integration, otherwise moreheating duty will be needed above desired energy target.

Hybrid Inter-Time-Inter-Systems Matching Procedures:

The hybrid inter-time inter-systems matching module/process, describedwith respect to FIGS. 3 and 13-can include the following steps:

Step 1 Conduct inter-time-zones energy matching. Step 2 Identify thethermal load to be integrated via intra-time integration and inter-timeintegration. Step 3 Define media of thermal load integration viainter-time zone integration. Step 4 Conduct intra-time inter-systemsenergy matches for each time zone. Step 4a Start theintra-time-inter-systems matching via de-lumping of each time zones gCCLand gHCL into its forming facilities, then plants, processes andstreams. Step 4b Conduct the intra-time-inter-systems matching thatachieve the defined intra-time zone thermal load integration using a“temperature duty diagram.”

Step 1 includes conducting inter-time-zones energy matches. FIG. 14illustrates an example of performing both direct and indirect matchingusing oil and/or water. According to one or more embodiments, it hasbeen shown that performing inter-time zone energy matching first,against conventional wisdom, and then intra-time zone matching providesmore potential for reducing energy utility consumption and GHGemissions.

Step 2 includes identifying the thermal load to be integrated viaintra-time integration and inter-time integration. Note, exemplaryprocedures applicable to inter/intra-time inter-systems energy matchingis provided in U.S. patent application Ser. No. 13/858,731 and U.S.patent application Ser. No. 13/858,718.

Step 3 includes defining the media of thermal load to be integrated viainter-time zone integration. Such media can include, but is not limitedto, thermal energy storage, rescheduling of activities or processes, andchanging of the flow rates.

Steps 4-4b include conducting intra-time inter-systems energy matchesfor each time zone. This step includes starting intra-time-inter-systemsmatching via de-lumping of each time zones gCCL and gHCL into itsforming facilities, then plants, processes and streams, and conductingintra-time-inter-systems matching that achieves the defined intra-timezone thermal load integration. This can be accomplished through use of a“temperature duty diagram” (see, e.g., FIG. 8), the construction ofwhich is described in detail in U.S. patent application Ser. No.13/858,731 and U.S. patent application Ser. No. 13/858,718.

Eco-Industrial Park Problem-Wide Representation and Lab Test Procedures:

The eco-industrial park problem wide representation and lab testprocedures module/method can incorporate the time-dependent processesinter-time zones energy integration and initial solution findingmodule/method 52, an eco-industrial parks membership management module54, an energy integration via temporal and spatial systems matchingmodule 55, a multi-time period eco-park utility system synthesis andoperation planning model module 56, and one or more of theprocesses/program modules 61 (FIG. 3). The eco-industrial park problemwide representation and lab test procedures can include the followingsteps:

Step 1 Define the eco-industrial park time and space problems Zones,Blocks, Facilities, Plants and Processes streams considered forinter-systems energy integration. Step 2 Use energy targeting module tofind [Qh] and [Qc] under all possible combinations of process-specificmodifications and stream-specific ΔT_min in the acceptable user definedrange, and use time-dependent processes inter-time zones energyintegration module and/or energy integration via temporal and spatialsystems matching module to obtain energy targets for intra- andinter-time and simultaneous space/systems energy integration. Step 3Locate the problem-wide pinch interval and the pinch-locationcontrolling processes/streams. Step 4 Decision maker selects/identifiesdesired level of energy target(s) for heating utility, cooling utilityor both. Step 5 Collapse the intervals when in interval form to locatethe problem-wide best/desired pinch, the pinch-location controllingprocess and the best process changes as well as streams-specific ΔT_minin the acceptable user defined range. Step 6 Define the user input ofabsolutely constrained/forbidden zones, facilities, plants, processesand streams matching (thermal load that must be handled via indirectintegration). Step 7 Use a eco-industrial park membership managementmathematical programming module to guide through best possible matchesamong the time and space zones, or blocks, or facilities, or plants, orprocesses Step 8 For very large number of processes and/or time zones,use a time-temperature duty-diagram to guide through the selection ofbest matches, as well.

Step 1 includes defining the eco-industrial park time and space problemsZones, Blocks, Facilities, Plants and Processes streams considered forinter-systems energy integration.

Step 2 includes using the energy targeting module 63 to find [Qh] and[Qc] under all possible combinations of process-specific modificationsand stream-specific ΔT_min in the acceptable user defined range, and usethe time-dependent processes inter-time zones energy integration module52 and/or energy integration via temporal and spatial systems matchingmodule 54 to obtain energy targets for intra- and inter-time and inter-and intra-space/systems energy integration.

Step 3 includes locating the problem-wide pinch interval and thepinch-location controlling processes/streams.

In Step 4, the decision maker reviews the data provided in Step 3 andselects/identifies the desired level of energy target(s) for heatingutility, cooling utility or both.

Step 5 includes collapsing the supply and demand intervals (when ininterval form) to locate the problem-wide best/desired pinch, thepinch-location controlling process or processes, and the best processchanges as well as streams-specific ΔT_min in an acceptable user definedrange.

Step 6 includes defining, typically through user input, the absolutelyconstrained/forbidden zones, facilities, plants, processes and streamsmatching (i.e., the thermal load or loads that must be handled viaindirect integration).

Step 7 includes using the eco-industrial park membership managementmathematical programming module 54 to guide through best possiblematches among the time and space zones, or blocks, or facilities, orplants, or processes.

Step 8 includes optionally using the time-temperature duty-diagram(e.g., FIG. 13) for very large number of processes and/or time zones, toassist in guiding the user through the selection of best matches, aswell.

FIGS. 10-12 provide a step-by-step example of the targeting andsolutions finding method. FIGS. 13-14 provide a graphical illustrationof displaying the problem and performing matching using thetemperature-time duty-diagram (T2D2). FIG. 10 includes a graphicalillustration of the problem whereby the data is organized as a cascadeof time steps (t1-t3) at individual temperature intervals (T1-T3). FIG.12 illustrates a clockwise rotation of the data illustrated in FIG. 10.

FIG. 12 provides a graphical illustration organized vertically bytemperature step and horizontally by time steps to provide for targetingand developing an initial solution through use of a combination of mediaof thermal load integration via inter-time zone integration. As showngraphically in the figure, optimal heat exchange can be achieved throughinter-time zone integration.

FIG. 13, introduced previously, illustrates application of the streamsdata listed in the Table 1, to a temperature-time duty-diagram. FIG. 14illustrates a combination of advanced matching with inter-time zoneintegration. In this example, optimal heat exchange can be achievedthrough rescheduling of stream t3-cold (“c”) to time period t1;rescheduling of stream t2-c to time period t3; rescheduling of streamt3-hot (“h”) to time period t2; storing the hot stream t1-h for use intime period t3; storing the hot stream t3-h to next batch and use startup heater for t2-c; storing the cold stream t2-c for use in time periodt3; using of a buffer stream such as hot oil to heat up t2-c and then tocool down t3-h; using of a buffer stream such as high pressure waterheat up t2-c and then to cool down t3-h; using the available steamboiler feed water system to cool t3-h; and manipulating the flowrate ofstream t2-c to be FCp=0.25 in t2 and FCp=1.75 in t3. Notably, the globalheating energy utility [Qh] requirement and global cooling energyutility [Qc] requirement are both zero.

FIGS. 15-17 illustrates three prior art methods of optimizing energyrecovery using the analysis model shown in FIG. 12 for comparativepurposes.

FIG. 15 illustrates application of a conventional intra-time zoneintegration energy targeting calculation to the data shown in Table 1.Notably, it can be seen that the global heating energy utility Qh andthe global cooling energy utility Qc are each 400 units.

FIG. 16 illustrates application of a conventional cascade analysisenergy targeting method to the data shown in Table 1. Although providingbetter results than the conventional intra-time zone integration energytargeting calculation, the global heating energy utility Qh and globalcooling energy utility Qc values, each 200 units, are still above thatprovided according to the embodiment of the methodology illustrated inFIGS. 10-12.

FIG. 17 illustrates application of a conventional time pinch energytargeting method to the data shown in Table 1. Similar to theconventional cascade analysis energy targeting method, althoughproviding better results than the conventional intra-time zoneintegration energy targeting calculation, the global heating energyutility Qh and global cooling energy utility Qc values, each 200 units,are still above that provided according to the embodiment of themethodology illustrated in FIGS. 10-12.

The energy targets calculations using both Time Pinch and CascadeAnalysis Methods render the same wrong results of minimum heating andcooling utilities, Q_heating (Qh)=200 units and Q_cooling (Qc)=200units, which are higher than the real global minima. Wang. Y. P., andSmith. R., “Time Pinch Analysis” Trans IChemE, vol 73, Part A, 1995. Thedifference between the two is: the Time Pinch method considers the timeconstraint, first, as a hard constraint, and the second “Cascadeanalysis” considers the temperature first. In the Time Pinch method, atank is used to move stream t1-H1 from t1 to t3, a low pressure steamstream is used for heating t2-C1 to desired target temperature and as acooling medium for t3-H2. In the Cascade Analysis method, a tank is usedto move stream t1-H1 from t1 to t2, and a high pressure steam stream isused for heating t3-C2 to desired target temperature and as a coolingmedium for t3-H2.

Mathematical Programming Model for the Eco-Industrial Park MembershipManagement:

The mathematical programming model can incorporate the eco-parksmembership management module 54 (FIG. 3). According to an exemplaryembodiment, the below formulation is solved successively to enumerateall possible combinations of solutions ranked from best objectivefunction value to least for each “user-selected” type of membership toidentify the elements of the eco-industrial park alliance/eco-industrialpark members. These elements can include, for example, plants and otheractivities in both space and time.

The model can include the following parameters:

1. Main Sets

A: is the set of all areas or time-zones in the problem

S: is the set of all streams in the problem

Area or Time-Zones Properties

qh_(a): hot utility needed for area a when pinched alone

qc_(a): cold utility need for area a when pinched alone

Stream Properties

st_(s): the supply temperature of steam s

tt_(s): the target temperature of stream s

fcp_(s): heat flow content of stream s

dtmin_(s): delta-min for stream s

${loc}_{s,x} = \{ \begin{matrix}1 & {{if}\mspace{14mu} s\mspace{14mu} {is}\mspace{14mu} {in}\mspace{14mu} {area}\mspace{14mu} a} \\0 & {otherwise}\end{matrix} $

Problem Configuration

n: number of tuples needed

c: cardinality of a tuple

Calculated Sets and Parameters

HS=(hs:hsεS and st_(hs)≧tt_(hs))

CS=(cs:csεS and sεHS)

xt: maximum supply or target temperatures among all streams

mt: minimum supply or target temperatures among all streams

T=(tεN:tε[xt,mt]), set of possible 1-degree wide temperature periods

G=(G₁, G₂, . . . , G_(n)), set of possible area groups

2. Variables

$x_{a,g} = \{ {{\begin{matrix}1 & {{if}\mspace{14mu} a\mspace{14mu} {is}\mspace{14mu} {assigned}\mspace{14mu} {to}\mspace{14mu} {group}\mspace{14mu} g} \\0 & {otherwise}\end{matrix}{TDem}_{t,g}} = {{{\underset{{{{{ext} > {st}_{cs}}\&}t} \leq {tt}_{ci}}{\Sigma}( {\underset{a\text{:}{loc}_{a,c,s}}{\Sigma}{x_{a,g} \cdot {fcp}_{cs}}} )}{TSup}_{t,g}} = {{\underset{{{{{hnt} > {tt}_{hs}}\&}t} \leq {st}_{hs}}{\Sigma}( {\underset{a\text{:}{loc}_{a,h,s}}{\Sigma}{x_{a,g} \cdot {fcp}_{hs}}} )}{TFeed}_{tg}{TSur}_{tg}}}} $

3. Constraints

One group for each area or time zone: Σ_(g)(x_(a,g))≦1 ∀_(a)εA

Group Size match tuple cardinality: Σ_(a)x_(a,g)=c ∀gεG

Period Feed Link: TFeed_(t,g)=TSur_(t-1g) ∀(t,g): t≠xt

Period Balance: TFeed_(t,g)+TSup_(t,g)−TDem_(t,g)−TSur_(t,g)=0

Objective Function

$\begin{matrix}{{obj} = {{\Sigma_{a}( {{qh}_{a} + {qc}_{a}} )} \cdot ( {1 - {\Sigma_{g}x_{a,g}}} )}} \\{{{+ \Sigma_{g}}T\mspace{14mu} {Feed}_{xtg}}} \\{{{+ \Sigma_{g}}T\mspace{14mu} {Sur}_{{{mt} + 1},g}}}\end{matrix}$

FIG. 18 illustrates a flow chart which describes an exemplaryimplementation of the mathematical programming model algorithm.According to the exemplary configuration, the computer reads the initialdata set (block 101), which can include the set of all areas ortime-zones and the set of all streams in the problem and theirproperties, and solves the mathematical program (block 102). If asolution is found (block 103), the solution is reported (block 104). Ifno solution is found, a report of infeasibility (block 105) is issued.If a next best alternative is needed (block 106), the solution is addedto the list of found solutions (block 107), the problem solver is askedto ignore the previous solution (block 108), and the mathematicalprogram is again executed (block 102).

Eco-Industrial Park Membership Management Program List:

An exemplary embodiment of the eco-industrial park membership managementprogram list is located in Appendix 2.

Domino-Effect Model for Low Pressure Steam Targeting Method:

The domino effect model can utilize the Domino-effect stream sharingmodule/method 53 (FIG. 3). According to an exemplary embodiment, thesteps of the model include:

Step 1 Allocating processes in a “mosaic” starting with the power plantor main cogeneration plant then followed by plants/facilities arrangedin the form of Demand-Supply-Demand and ending by plant Demand. Step 2Steam is transferred from one door to the next door primarily orcompletely only to avoid long distances and steam condensation. Step 3Highlight in-process modifications that can be performed to enhanceprocess/plant' capability in producing more steam or whose status can bechanged from demanding to supplying or vice versa. Step 4 Plants arearranged by their geographical locations and such location will bedecided after conducting the targeting phase calculation and guided bystep one in grassroots applications. Step 5 Three steam targets arecalculated: A. No steam transfer from one plant to another target, B.Steam is only transferred to the next door plant target, and C. Steamwheeling target selected using the “Domino-Effect” targeting methodsteps 1-4.

According to Step 1, and as perhaps best shown in FIG. 19, processes arepreferably allocated in a “mosaic” starting, for example, with thecentral power and steam facility or main cogeneration plant 121 thenfollowed by plants/facilities 123 (P1-P6) arranged in the form of demandD-supply S-demand D and ending by demand D. In this example, “S”indicates the facility low-pressure steam generation or in-planinstalled/dedicated cogeneration/boilers low-pressure steam supply; “D”indicates the plant/facility low-pressure steam demand, and “EE” (e.g.,EE1-EE6) indicates the external steam energy requirement for therespective plants/facilities.

In Step 2, steam is transferred from one door to the next door primarilyor completely only to avoid long distances and steam condensation.

In Step 3, in-process modifications that can be performed to enhanceprocess/plants capability in producing more steam, or whose status canbe changed from demanding to supplying or vice versa are highlighted.

In Step 4, plants 123 are arranged by their geographical locations andsuch location will be decided after conducting the targeting phasecalculation and guided by step one in grassroots applications. Forexample, if it is determined that it is desirable to share steam betweenplants P1 and P2, particularly if the design is a new eco-industrialpark design, to the extent feasible, it would be beneficial to positionthe plants adjacent each other to avoid the long distances and steamcondensation, and to continue passing steam door-to-door to other plantsP3-P5.

In step 5, according to an exemplary configuration, three potentialsteam targets are calculated to determine the optimal steam transferconfiguration. Potential steam targets include: No steam is transferredfrom one plant to another target; Steam is only transferred to the nextdoor plant target; and Steam wheeling target is selected using this“Domino-Effect” targeting process.

FIG. 20 graphically illustrates an example model of a scenario where nosharing occurs and the steam deficit is obtained only from the centralpower and steam facility 121. FIG. 21 graphically illustrates an examplemodel of a scenario where the steam deficit is obtained from a next-doorplant 123 and/or the central power and steam facility 121.

FIG. 22 graphically illustrates a no sharing solution example indicatinga requirement of 15 units of external energy from the central power andsteam facility 121. FIG. 23 graphically illustrates a next-door onlybased sharing solution example utilizing the steam supply and demandvalue scenario of FIG. 21. Although requiring less external energy, thenext-door only-based sharing solution still required a total externalenergy of 12 units. FIG. 24 graphically illustrates a “domino effect”low-pressure steam sharing solution example utilizing the steam supplyand demand value scenario of FIGS. 22 and 23. Notably, in this exemplaryscenario, the “domino effect” solution requires only 40% of that of theconvention no-steam sharing solution, and only 50% of that of theconventional “next-door only” based sharing solution.

Multi-Levels-Multiple Facilities Steam Targeting Module/Method:

This calculation provides multi-level multi-facilities global minimumsteam supply and demand targeting under uncertainties for multipleplants for the entire eco-industrial park. This calculation iscomplementary to the Domino-Effect calculation for low pressure steamintegration. The below described calculations can be accomplished viaadding steam supply and steam demand of all plants at each level andthen executing the cascade calculations described, for example, in U.S.patent application Ser. No. 12/480,415, titled “System, Program Product,and Related Methods for Global Targeting of Process Utilities UnderVarying Conditions,” using real numbers or intervals. This procedurebeneficially enables the user to decide on/select the best allocation ofplants in the planning of new eco-industrial parks. The multi-levelsmulti-facilities steam targeting module/method, described with respectto FIGS. 25-27, can include the following steps:

Step 1 Extract all the heating and cooling tasks in the wholeeco-industrial park activities and calculate required steam supply anddemand levels and loads for all plants. Step 2 Establish a supply(s)-demand (d)-cascade from steam supply and demand loads at each steamlevel. Step 3 Use step # 2 to: (a) Calculate “S” supply and “D” demandat each steam level (HPS, MPS, and LPS) for the whole of theeco-industrial park via cascading supply “s” and demand “d” inspace/plant number; (b) Define plants' arrangements which minimize steamtransportation; and (c) Identify the amount of steam to be transferredfrom one plant to another to achieve global minimum steam demand beforesteam letdowns. Step 4 Use step # 2 to calculate global minimum steamsupply/generation and waste for the whole of the eco-industrial parksindustrial and non-industrial activities.

FIG. 25 provides a graphical illustration of a model for visualizing thecalculation of the global minimum steam supply and demand for aneco-industrial park.

In Step 1 includes extracting all significant heating and cooling tasksin the entirety of the eco-industrial park activities and calculatingrequired steam supply and demand levels and loads for all plants. Thefollowing table, Table 2, illustrates data for a four-plant example, asfollows:

TABLE 2 Plant/Steam Level Generation (10{circumflex over ( )}4 Lb/h)Demand (10{circumflex over ( )}4 Lb/h) P1 HPS 1 2 MPS 3 0 LPS 4 0 P2 HPS3 1 MPS 0 5 LPS 0 3 P3 HPS 1 4 MPS 1 0 LPS 2 0 P4 HPS 1 6 MPS 0 3 LPS 10

The table lists data for a sharing and non-sharing scenario ofmulti-levels multiple facilities steam targeting. The scenario includesthree steam headers (HPS, MPS, LPS) at plants “P1”-“P4” positioned inorder of distance, and having the above steam generations capabilitiesand demand requirements as listed at each level.

Step 2 includes establishing a supply (s)-demand (d)-cascade from steamsupply and demand loads at each steam level such as, for example, usingthe model illustrated in FIG. 25.

Step 3 includes utilizing the supply (s)-demand (d)-cascade of step #2:(a) to calculate the total header “S” supply and “D” demand at eachsteam level (HPS, MPS, and LPS) for the whole of the eco-industrial parkproblem (e.g., S1-S3, D1-D3 in this example) via cascading process-levelsupply “s” and demand “d” in space/plant number (e.g., P1-P4 in thisexample); (b) to define the plants' arrangements which minimize steamtransportation; and (c) to identify the amount of steam to betransferred from one plant P1-P4 to another to achieve global minimumsteam demand before steam letdowns.

Step 4 includes utilizing the supply (s)-demand (d)-cascade of step #2to calculate the global minimum steam supply/generation and waste forthe whole of the eco-industrial park's industrial and non-industrialactivities.

FIG. 26 illustrates a non-sharing scenario of multiple steamlevels-multiple intra-facilities steam calculation example using thedata of Table 2. In this example, it can be seen that the steam demandon the high-pressure steam headers is 18 units and the low-pressuresteam generation/waste is 11 units.

FIG. 27 illustrates a sharing scenario of multi-levels multipleinter-facilities steam targeting calculation example according to anembodiment of the invention, using the data of Table 2. In this example,it can be seen that the high-pressure steam demand is reduced to fiveunits, and the steam generation/waste is reduced to four units.

Eco-Industrial Park Energy Targeting:

FIGS. 28-51 provide a detailed example of eco-industrial park energytargeting according to one or more embodiments of the invention. FIG. 28illustrates an example of a data table 129 including the task type,stream identification and its initial identity, starting temperature,target temperature, heat capacity flowrate, duration, schedule, and heatcapacity. This data can be inputted separately or through an automatedprocess to populate values in a energy consumption calculationwebpage/webpage form 130 (see, e.g., FIG. 29) for calculating the globalminimum energy consumption.

The energy consumption calculation webpage form 130 shown in FIG. 29includes a list of streams 131, their type 132, their startingtemperature interval values 133, their target temperature intervalvalues 134, their heat capacity flow rate interval 135, and theirminimum and maximum entropy values 136, 137, the global minimum coolingand heating utilities requirements 138, 139, the pinch location/interval141, and a global ΔT_min 142 and its marching interval.

FIG. 30 provides a graphical illustration of the energy consumptioncalculation webpage form 130 restricted to provide stand-alone batchplant energy targeting calculations such as, for example, minimumcooling and heating utilities and pinch location/interval values. FIG.31 provides a graphical illustration of the energy consumptioncalculation webpage form 130 restricted to provide stand-alone housingcompound energy targeting calculations. FIG. 32 provides a graphicalillustration of the energy consumption calculation webpage form 130restricted to provide stand-alone hospital compound energy targetingcalculations. FIG. 33 provides a graphical illustration of the energyconsumption calculation webpage form 130 restricted to providestand-alone chemical process I, continuous, energy targetingcalculations. FIG. 34 provides a graphical illustration of the energyconsumption calculation webpage form 130 restricted to providestand-alone chemical process II, continuous, energy targetingcalculations. FIG. 35 provides a time interval graph of the dataprovided in data table 129 (FIG. 28) used for graphically identifyingstreams in both time and space for inter-time-zones energy integration.FIG. 36 provides another example of a data table 149 having the streamname pre-organized to reflect stream type and associated time zone. FIG.37 provides an example of time zones stream data mapping of the dataprovided in data table 149 (FIG. 36).

FIG. 38 provides an example of an energy consumption calculation webpageform 150 illustrating intra-time zone energy targeting for space zone 1.FIG. 39 provides an example of the energy consumption calculationwebpage form 150 illustrating intra-time zone energy targeting for spacezone 2. FIG. 40 provides an example of the energy consumptioncalculation webpage form 150 illustrating intra-time zone energytargeting for space zone 3. FIG. 41 provides an example of the energyconsumption calculation webpage form 150 illustrating intra-time zoneenergy targeting for space zone 4. FIG. 42 provides an example of theenergy consumption calculation webpage form 150 illustrating intra-timezone energy targeting for space zone 5. FIG. 43 provides an example ofthe energy consumption calculation webpage form 150 illustratinginter-time zone energy targeting.

FIGS. 44-51 provide an example of an inter-area, inter-time targetingwebpage form 160, which provides for the calculation of best and nextbest coupling between two or more zones in one or more groups. Thewebpage form 160 includes an input field 161 allowing input of thenumber of groupings of zones (number of tuples) and the number of zonesto be matched (tuple cardinality). The webpage form 160 also includesinput fields such as, for example, buttons 162-165 which allow forselecting an automated solvent of the problem, button 162, the provisionof the next best solution, button 163, a reset, button 164, and a pinchzone identification, button 165. The webpage form 160 also includesoutput fields including an output field 167 which outputs anidentification of the best or next best matched zones and one or moregroups, and output field 168 which outputs an energy consumptionobjective, or alternatively, an energy savings objective.

Particularly, FIG. 44 illustrates a best coupling between two time zonesdetermination identifying the zones providing the best coupling. FIG. 45illustrates a second best coupling between two time zones determination.FIG. 46 illustrates best two couplings between two time zones. FIG. 47illustrates second best two couplings between two time zones. FIG. 48illustrates integration between three time zones. FIG. 49 illustratessecond best integration between three time zones. FIG. 50 illustratesintegration between four time zones. FIG. 51 illustrates second bestintegration between four time zones. One of ordinary skill in the artwill recognize that there can be as many times zones as required toprovide for readily matching the zones both temporally and spatially.

Eco-Industrial Park Inter-Time Zones (Temporal) Integration SolutionsFinding:

FIGS. 52-62 provide a detailed description of eco-industrial parkinter-time zones integration solution finding via temporal and spatialsystems matching. According to an exemplary embodiment, this process caninclude application of the energy integration via temporal and spatialsystem matching module 55 to provide integration and matching options,an employment of the temperature time duty diagram (T2D2) to providevisualization to enhance finding the inter-time zones integrationsolution, and a temperature duty diagram (TD2) to provide visualizationof spatial integration in the time zones.

Particularly, FIG. 52 illustrates a temperature time duty diagram (T2D2)containing the data listed in data table 149 (see, e.g., FIGS. 36-37),above and below the controlling pinch (100° F.) shown at 171. FIG. 53illustrates the T2D2 displaying an above-the-pinch inter-time zone(temporal) integration option in which zones t1 and t2 cold areintegrated with t3, t4, and t5 hot. FIG. 54 illustrates an alternateintegration option in which t3 hot is instead integrated with t4 cold.FIG. 55 illustrates another alternate integration option in which t4 hotis instead integrated with t5 cold. FIG. 56 illustrates anotheralternative integration option in which t4 hot is instead integratedwith t5 cold and t3 hot is integrated with t4 cold.

FIG. 57 illustrates a time duty diagram (TD2) containing the data listedin data table 149 for time zone t1, above and below the controllingpinch. FIG. 58 illustrates the TD2 of FIG. 57 displaying anabove-the-pinch inter-processes (spatial) integration option in whichChemical Continuous Process (CH)-2 hot process integrates with CH-1 andCH-Batch cold process and the Housing and Hospital hot processes eachintegrate with CH-1 and CH-Batch processes. FIG. 59 illustrates analternative spatial integration option in which CH-2 hot integrates withCH-Batch cold. FIG. 60 illustrates another spatial integration option inwhich CH-2 hot integrates with CH-1 and CH-Batch cold. FIG. 61illustrates another spatial integration option similar to that shown inFIG. 60 but with the Housing hot process further integrating with theCH-Batch cold process. FIG. 62 illustrates another spatial integrationoption similar to that shown in FIG. 61 but with the Hospital hotprocess further integrating with the CH-Batch cold process.

Multi-Time-Period Combined Heat and Power Model for Eco-Industrial ParkUtility System Synthesis and Planning Under Uncertainty:

One or more embodiments of the invention provide a multi-time-period(MTP) combined heat and power (CHP) model (MTP_CHP) for theeco-industrial park utility system synthesis and planning underuncertainty. The MTP_CHP for eco-industrial park utility systemsynthesis provides an advancement over the methods, systems, and programcode for enhancing energy efficiency via systematic hybridinter-processes integration described in U.S. patent application Ser.No. 13/858,731 and U.S. patent application Ser. No. 13/858,718, andexpands upon the methods, systems, and program code for simultaneousprocess and utilities syntheses in partially and fully decentralizedenvironments described in U.S. patent application Ser. No. 13/757,467and U.S. patent application Ser. No. 13/757,491. According to one ormore embodiments, the model is not only limited in its analysis to asingle facility, but rather, can provide the optimum configuration ofutilities system for an industrial city(s), including severalindustries, buildings, communities. The total energy demand andin-plants generation is significantly and substantially different thanthat in one plant/facility. Additionally, the model accounts for thedemand and/or in-plants generation which can be composed of continuousand batch processes/tasks which provide a wide range of operatingwindows, and the utilities complex can provide this demand all the timein the most efficient and capital cost effective way.

FIG. 63 illustrates a process developed to accompany the optimumsynthesis and planning of the eco-industrial park utilities complex.Several new constraints are considered such as, for example, thestability of supply for both power and steam. During the loss of onemajor unit supplying power or steam, the demands should be met at anypoint of time. Hence, according to one or more embodiments, to formulatethe most optimum configuration, the location, number and sizes of majorequipment of the utilities system are to be addressed globally for thesynthesis and not at the same time zone, independently. Once thesynthesis decision/task is satisfied, another important consideration tobe addressed is then the optimum operation at each time zone.

Specifically, the process includes beginning with a listing of allfacilities, plants, buildings, houses, etc. in the eco-industrial park(block 201), followed by gathering/retrieving steam and power demandranges for the whole site (block 202), which can include gathering thesteam production from process heaters and other waste heat streams. Theprocess can also include utilizing maximum values as the designrequirements for the optimum configuration of utilities system at eachtime zone steam and/or power demands (block 203), and analyzing thestability constraints and reliability requirements and/or determiningpotential location utilities complex (block 204). The stability indexwould be given at each possible site, at which the configuration has tosatisfy this index at all times. Based upon the cost and benefits, theoptimization algorithm of the utilities complex will determine thedesign configuration of the utility system boilers, cogeneration units,and steam turbines or power generation, among others (block 205).According to the exemplary configuration, the process includesdetermining the sizes and number of major units of the utilitiescombined heat and power complex at their respective locations as thefinal output (block 207).

FIG. 64 includes an exemplary industrial city total steam demand tableincluding range data representing hourly consumption for a typical dayfor multiple facilities including industrial plants, hospitals, andcommercial buildings. FIG. 65 includes an exemplary industrial citytotal power demand table including range data also representing hourlyconsumption for a typical day. Note, although described as beingprovided hourly, the time period can be shorter or larger depending uponthe needs of the user as would be understood by one of ordinary skill inthe art.

1. CHP Design Formulation:

According to one or more embodiments, for effective eco-industrial parkutility system synthesis, the utilities design considers the majorcomponents of the eco-industrial parks and is not limited to any onefacility/complex. In the context of the eco-industrial park utilitysystem, the steam and power demands generated per hour as a summation ofindependent users. Users include other industrial plants, buildings,residential houses, hospital and others. Some of the demand is batchprocessing, whereby the demand is not continuous. The utilities designcan beneficially consider the entire complex requirements and try tosatisfy the peak demands, while at the same time, remaining lien enoughto satisfy low and average demand requirements without retaining anunreasonable amount of excess capacity.

Appendix 3 includes an exemplary model structure including: data sets(original and derived); parameters; variables; and process coolingdemand and objectives (minimum total cost and minimum total operatingcosts) calculations.

2. CHP Number of Headers Selection:

According to an exemplary configuration, steam headers loadsidentification utilizes the CHP algorithm to calculate the utilitysystem total annualized cost (USTAC) for 2, 3, 4, 5, 6 and 7 headersunder all possible combinations of process design changes. This isdescribed, for example, with respect to FIGS. 10A-11 of U.S. patentapplication Ser. No. 13/757,467 and accompanying text, incorporated byreference.

3. CHP Data Input:

According to one or more embodiments, the typical model input dataincludes: the equipment name and minimum/maximum operating capabilities(FIG. 66); number of steam headers definition (FIG. 67); listing andtype of motor, rating, and efficiency, and listing and type of steamturbine, rating, and steam rate (FIG. 68); along with CHP model inputdata describing process stream demand intervals, process streamgeneration intervals, power demand intervals, available fuel andoperating cost, and power export intervals (FIG. 69).

4. CHP Output:

According to one or more embodiments, the output from the CHP sub-modelcan include: the number of headers and its operating conditions; thenumber of cogeneration units and its sizes; the number of boilers andsizes; the number of steam turbine generators and its capacities; thenumber of motors and steam turbines (for process equipment driving) andits sizes; the size and location of solar system; the at least close tooptimal utility subsystem steam and power generation and allocation; andthe at least close to optimal in-process steam demand and generation.Other output model features as understood by those of ordinary skill inthe art can also be included.

It is important to note that while the foregoing embodiments of thepresent invention have been described in the context of a fullyfunctional system and process, those skilled in the art will appreciatethat the mechanism of at least portions of the present invention and/oraspects thereof are capable of being distributed in the form of acomputer readable medium in a variety of forms storing a set ofinstructions for execution on a processor, processors, or the like, andthat various embodiments of the present invention apply equallyregardless of the particular type of media used to actually carry outthe distribution. Examples of the computer readable media include, butare not limited to: nonvolatile, hard-coded type media such as read onlymemories (ROMs), CD-ROMs, and DVD-ROMs, or erasable, electricallyprogrammable read only memories (EEPROMs), recordable type media such asfloppy disks, hard disk drives, CD-R/RWs, DVD-RAMs, DVD-R/RWs,DVD+R/RWs, HD-DVDs, memory sticks, mini disks, laser disks, Blu-raydisks, flash drives, and other newer types of memories, and certaintypes of transmission type media such as, for example, digital andanalog communication links capable of storing the set of instructions,with the exception of those considered to be non-statutory subjectmatter. Such media can contain, for example, both operating instructionsand the operations instructions related to the program code 51, and thecomputer executable portions of the method steps according to thevarious embodiments of methods of providing enhanced energy efficiencyand reduced greenhouse gas emissions for an eco-industrial park through,for example, advanced hybrid inter-time zone inter-systems/processesenergy integration targeting and solutions generation, among others,described above.

The terms “substantially” and “approximate” with reference to valuesgenerally refer to reasonably proximate or exact values.

In the drawings and specification, there have been disclosed a typicalpreferred embodiment of the invention, and although specific terms areemployed, the terms are used in a descriptive sense only and not forpurposes of limitation. The invention has been described in considerabledetail with specific reference to these illustrated embodiments. It willbe apparent, however, that various modifications and changes can be madewithin the spirit and scope of the invention as described in theforegoing specification.

APPENDIX 1

The following include related patents and patent applications eachincorporated herein by reference in its entirety: U.S. Pat. No.7,698,022, System, Method, and Program Product for Targeting and OptimalDriving Force Distribution in Energy Recovery Systems; U.S. Pat. No.7,873,443, System, Method and Program Product for Targeting and OptimalDriving Force Distribution in Energy Recovery Systems; U.S. Ser. No.12/480,415, Method and Software for Global Targeting of ProcessUtilities under Varying Condition; U.S. Pat. No. 8,032,262, System,Method, and Program Product for Synthesizing Non-Constrained andConstrained Heat Exchanger Networks; U.S. Pat. No. 7,729,809, System,Method, and Program Product for Targeting and Identification of OptimalProcess Variables in Constrained Energy Recovery Systems; U.S. Ser. No.12/898,461, Systems, Program Product, and Methods for Synthesizing HeatExchanger Networks that Exhibit Life-Cycle Switchability and Flexibilityunder all Possible Combinations of Process Variations; U.S. Ser. No.61/256,754, System, Method, and Program Product for SynthesizingNon-Thermodynamically Constrained Heat Exchanger Networks; U.S. Ser. No.61/256,754, System, Method, and Program Product for Synthesizing HeatExchanger Networks and Identifying Optimal Topography for FutureRetrofit; U.S. Ser. No. 12/898,484, Systems, Program Product, andMethods for Targeting Optimal Process Conditions that Render an OptimalHeat Exchanger Network Design Under Varying Conditions; U.S. Ser. No.12/898,475, Systems, Program Product, and Methods for Synthesizing HeatExchanger Networks that Account for Future Higher Levels of Disturbancesand Uncertainty, and Identifying Optimal Topology for Future Retrofit.

APPENDIX 2 SECTION /* _Model */  DECLARATION SECTIONProblem_Configurations   ELEMENT PARAMETER:    identifier :required_num_of_tuples    range  : Integers    initial data : 1 ;  ELEMENT PARAMETER:    identifier : required_tupple_cardianlity   range  : Integers    initial data : 2 ;  ENDSECTION ;  DECLARATIONSECTION Math_Program   VARIABLE:    identifier : Obj    range  : free   definition : sum(a , ( area_qh(a) + area_qc(a)) * ( 1− sum( g, area_assigned_to_group(a, g))) )        + sum(g, period_feed(max_temp,g))        + sum(g, period_surplus(min_temp + 1 , g)) ;   MATHEMATICALPROGRAM:    identifier : minimize_obj    objective : Obj    direction :minimize    constraints : AllConstraints    variables : AllVariables   type  : Automatic ;  ENDSECTION ;  DECLARATION SECTIONCalculated_Parameters   PARAMETER:    identifier : stream_count_in   index domain : (a)    definition : count(s in streams_in(a)) ;  PARAMETER:    identifier : max_temp    range  : integer   definition : max(max(hs,supply_temp(hs)−dtmin(hs)), max(cs,target_temp(cs))) ;    PARAMETER:    identifier : min_temp   range  : integer    definition : min(min(hs,target_temp(hs)−dtmin(hs)),  min(cs,supply_temp(cs))) ;  ENDSECTION ; DECLARATION SECTION Calculated_Sets   SET:    identifier : streams_in   index domain : (a)    subset of : streams    definition : {s |stream_in_area(s, a)} ;   SET:    identifier : periods    subset of :Integers    indices  : t, t_1    order by : −t    definition : {min_temp+1 .. (max_temp)} ;   SET:    identifier : groups    index  : g   definition : elementrange(1,required_num_of_tuples, 1,    “Group_”) ; ENDSECTION ;  DECLARATION SECTION Problem_Vars   VARIABLE:   identifier : period_demand    index domain : (t,g)    range  : free   definition : sum(cs| t > supply_temp(cs) and t <=    target_temp(cs),          sum(a | stream_in_area(cs, a),         area_assigned_to_group(a, g)) *  fcp(cs)        ) ;   VARIABLE:   identifier : period_supply    index domain : (t,g)    range  : free   definition : sum(hs| t > target_temp(hs)−dtmin(hs) and t <=   supply_temp(hs) ,          sum(a | stream_in_area(hs, a),         area_assigned_to_group(a, g)) *  fcp(hs)        ) ;   VARIABLE:   identifier : period_feed    index domain : (t,g)    range  :nonnegative ;   VARIABLE:    identifier : period_surplus    index domain: (t,g)    range  : nonnegative ;   VARIABLE:    identifier :area_assigned_to_group    index domain : (a,g)    range  : binary ; ENDSECTION ;  DECLARATION SECTION Problem_Constraints   CONSTRAINT:   identifier : one_group_for_area    index domain : (a)    definition :sum(g, area_assigned_to_group(a, g)) <= 1 ;   CONSTRAINT:   identifier : group_size_match_tuple_cardinality    index domain : (g)   definition : sum(a , area_assigned_to_group(a, g)) = required_tupple_cardianlity ;   CONSTRAINT:    identifier :period_feed_surplus_link    index domain : (t,g) | t <> max_temp   definition : period_feed(t,g) = period_surplus(t−1, g) ;  CONSTRAINT:    identifier : period_balance    index domain : (t,g)   definition : period_feed(t,g) + period_supply(t,g)=       period_surplus(t,g) + period_demand(t,g) ;  ENDSECTION ; DECLARATION SECTION Cutting_Constraints  ENDSECTION ; ENDSECTION /*_Model */ ; SECTION /* Main_Data */  DECLARATION SECTION Main_Parameters  PARAMETER:    identifier : dtmin    index domain : hs ;   PARAMETER:   identifier : BigM    range  : nonnegative    definition :1.2*max_temp ;   PARAMETER:    identifier : supply_temp    index domain: (s) ;   PARAMETER:    identifier : target_temp    index domain : (s) ;  PARAMETER:    identifier : fcp    index domain : (s) ;   PARAMETER:   identifier : stream_in_area    index domain : (s,a)    range  :binary ;  ENDSECTION ;  DECLARATION SECTION Main_Sets   SET:   identifier : hot_streams    subset of : streams    index  : hs   definition : {s | target_temp(s) <= supply_temp(s)} ;   SET:   identifier : cold_streams    subset of : streams    index  : cs   definition : {s | target_temp(s) >= supply_temp(s)} ;   SET:   identifier : areas    index  : a ;   SET:    identifier : streams   index  : s ;  ENDSECTION ; ENDSECTION /* Main_Data */ ; PROCEDURE  identifier : MainExecution   body  :   solve minimize_obj ENDPROCEDURE;

APPENDIX 3

Original Sets:

HDR: Steam headers.

BLR: Boilers.

COGEN: Cogeneration Units.

SOLAR: Solar thermal units

STG: Steam turbine generator units.

CSTG: Condensing steam turbine generator units.

BOS: Break over stations.

COND: Condensers

PST: Process steam turbines.

MSwitch: Motors switchable to process steam turbines

PSGen: Process steam generators.

PCDem: Process cooling demand

FUEL: Fuel types

Derived Sets:

BLRHDR[BLA×HDR]: Matching between each boiler and the header it isconnected to.COGENHDR[COGEN×HDR]: Matching between each cogen and the headerconnected to.SOLARHDR[SOLAR×HDR]: Matching between each Solar thermal unit and theheader connected to.STGInHDR[STG×HDR]: Input steam header to the STG.STGOutHDR[STG×HDR]: Output steam header from the STG.CSTGHDR[CSTG×HDR]: Input steam header to the CSTG.BOSIn[BOS×HDR]: Input steam header to the breakover station.BOSOut[BOS×HDR]: Output steam header of the breakover station.CONDHDR[COND×HDR]: Condenser Input steam header.DEAStmHDR[HDR]: Deaerator steam header.PSTInHDR[PST×HDR]: Inlet steam header to process steam turbine.PSTOutHDR[PST×HDR]: Outlet header from process steam turbine.PSGenHDR[PSGen×HDR]: Outlet header from process steam generator.

Parameters

Seam Headers:

HDRPres[iεHDR]: Header pressure.HDRTemp[iεHDR]: Header temperature.HDRLoss[iεHDR]: % loss of steam from header,HDRRet[iεHDR]: Steam returning from process to header (flash recovery).HDRBfw[iεHDR]: BFW to a steam headerHDRMaxDem[iεHDR]: Maximum process steam demand on a headerHDRMinDem[iεHDR]: Minimum process steam demand on a headerHDREnth[iεHDR]: Enthalpy of a steam header.HDRCost[iεHDR]: Cost of header

Boilers:

BLRCap[iεBLR]: Steam generation capacity of boiler.BLRnMin[iεBLR]: Minimum allowable steam generation rate for an operatingboiler.BLRc0[iεBLR]: Boiler fuel consumption constant coefficient.BLRc1[iεBLR]: Boiler fuel consumption linear coefficient.BLRc2[iεBLR]: Boiler fuel consumption quadratic coefficient.BLRCC[iεBLR]: Boiler's cycle of concentration.BLRLoss[iεBLR]: Boiler's % loss of boiler feed water,BLRPrice[iεBLR]: Annualized capital cost of boiler of the given specs.

Cogeneration:

COGENCap[iεCOGEN]: Power generation capacity of the cogen unit.COGENMin[iεCOGEN]: Minimum power generation of an operational cogenunit.COGENStmRatio[iεCOGEN]: Steam to power ratio of the cogen unit.COGENc0[iεCOGEN]: Fuel consumption constant coefficient.COGENc1[iεCOGEN]: Fuel consumption linear coefficient.COGENc2[iεCOGEN]: Fuel consumption quadratic coefficient.COGENCC[iεCOGEN]: Cogen's cycle of concentration parameter for the HRSG,COGENLoss[iεCOGEN]: Water loss from cogen unit as a % of BFW,COGENPrice[iεCOGEN]: Annualized capital cost of a cogen units of thegiven specs.

Steam Turbine Generator:

STGEff[iεSTG]: Isentropic efficiency of the steam turbine generator.STGCap[iεSTG]: Steam capacity of STG.STGLoss[iεSTG]: % of steam loss from STG.STGEnthIn[iεSTG]: STG input steam enthalpy from input steam header.STGEnthOut[iεSTG]: STG output steam enthalpy.STPrice[iεSTG]: Annualized capital cost of an STG unit of the givenspecs,

Condensing Steam Turbine Generator:

CSTGEff[iεCSTG]: Isentropic efficiency of the condensing steam turbinegenerator.CSTG[iεCSTG]: Steam flow capacity through the CSTG.CSTGLoss[iεCSTG]: % of steam loss from CSTG.CSTGStmEnthIn[iεCSTG]: Enthalpy of input steam to the CSTG.CSTGStmEnthOut[iεCSTG]: Enthalpy specs of the steam out of the CSTG (outof the STG stage).CSTGWtrEnth[iεCSTG]: Enthalpy specs of condensate water of CSTG.CSTGDutyEnth[iεCSTG]: Enthalpy of duty of condensed water of CSTG.CSTGPrice[iεCSTG]: Annualized capital cost of CSTG.

Breakover Station:

BOSCap[iεBOS]: Seam capacity of the breakover station.BOSLoss[iεBOS]: % of steam loss from the BOS.BOSStm[iεBOS]: Steam flow to BOSBOSEnth[iεBOS]: Enthalpy of BOS steam.BOSPRice[iεBOS]: Annualized capital cost of a BOSS of the given specs.

Condenser:

CONDCap[iεCOND]: Capacity of steam flow through the condenser,CONDLoss[iεCOND]: % loss of steam flow through the condenser.CONDStm_x[iεCOND]: Steam quality at the condenser output.CONDEnth[iεCOND]: Enthalpy of condenser output.CONDEnthDuty[iεCOND]: Enthalpy of condenser duty.CONDPrice[iεCOND]: Annualized capital cost of a condenser unit with thegiven specs.

Process Steam Turbine:

PSTLoss[iεPST]: % loss of steam flow through PST.PSTDem[iεPST]: Steam demand for the PST.PSTEnth[iεPST]: Enthalpy of the outlet steam from the PST.

Switchable Motors to Process Steam Turbines:

MSwitchHp[iεMSwitch]: HP required by process driven by switchable motorsMSwitchEff[iεMSwitch]: Efficiency of switchable motorsMSwitchMWToPST[iεMSwitch]: Power demand in motors switchable to ProcessSteam TurbinesMSwitchStmToPST[iεMSwitch]: Steam flow to process steam turbinesswitchable with

Process Steam Generator:

PSGenEnth[iεPST]: Enthalpy of outlet steam from process steam generator,PSGenMaxProd[iεHDR]: Maximum Steam production rate of process steamgenerator.PSGenMinProd[iεHDR]: Minimum Steam production rate of process steamgenerator.

Solar Thermal Unit:

SOLARfwEnth[iεSOLAR]: BFW Enthalpy to solar thermal unitSOLAROutEnth[iεSOLAR]: Enthalpy of Hot water or steam generated fromsolar thermal unitSOLARStm_x[iεSOLAR]: Quality of steam generated from solar thermal unitSOLAREff[iεSOLAR]: Efficiency of Solar thermal unitSOLARRad[iεSOLAR]: Avg. Daily heat radiation from sun (kwh)SOLARCost[iεSOLAR]: Annualized cost of Solar thermal unit

Condensate System:

SkimTankLoss: % losses from skim tank.MWWtrEnth: Enthalpy of the makeup water.CondRetFlow: Flow rate of the return condensate,CondCoolerLoss: % loss of condensate from condensate coolers.CondRetTargEnth: The target enthalpy of the return condensate.

Deaerator:

DEAStm: Steam flow to the deaerator.DEAStmEnth: Enthalpy of the steam used in the deaerator.DEAOutWtrEnth: Enthalpy of the water leaving the deaerator.DEALoss: % loss of water from dearator.DEAVentFlow: Flow rate of steam vented from the deaerator.DEAVentEnth: Enthalpy of the steam vented from the deaerator.

Power:

TotPwrDem: Power demand from the process (fixed and variable loads).OtherPwrDem: Power demand for other than process (other industrial powerdemands buildings, hospital, residential houses, masgid, etc)

Fuel:

FuelType[iεFuel]: Type of fuelsFuelMaxAv[iεFuel]: Maximum quantity of a fuel typeFuelHV[iεFuel]: Heating value of a fuel typeFuelPrice[iεFuel]: Price of a fuel type

Economics:

PriceImpPwr: Imported power price.PriceExpPwr: Exported power pricePriceMUWtr: Make up water price.

Variables:

Steam Headers:

HDRIn[iεHDR]: Steam flow into header.HDROUT[iεHDR]: Steam flow out of header.HDRBFW[iεHDR]: Boiler feed water injected into header to maintain headerenthalpy specs.HDRDem[iεHDR]: Process & all other steam demand on a header; Determineoptimal values of Steam for heating demand at different headers within agiven intervals

Boilers:

BLROn[iεBLR]: Binary variable to determine whether the size of a boilerselected (on/off) (Binary).BLRBFW[iεBLR]: Boiler feed water into boiler.BLRSTM[iεBLR]: Boiler steam generation rate.BLRBD[iεBLR]: Blowdown from boiler.BLRFuel[iεBLR]: Boiler's fuel consumption rate.BLRNo[iεBLR]: Number of installed units of the boiler (Nonnegativeinteger.

Cogeneration:

COGENOn[iεCOGEN]: Binary variable to determine whether a cogen unit ison or off (Binary).COGENPwr[iεCOGEN]: Power generation rate from cogen unit.COGENBFW[iεCOGEN]: Boiler feed water to cogen unit,COGENStm[iεCOGEN]: Steam generation rate from cogen unit.COGENBD[iεCOGEN]: Water blowdown rate from cogen unit.COGENFuel[iεCOGEN]: Fuel consumption rate of cogen unit.COGENNo[iεCOGEN]: Number of installed cogen units (Nonnegative integer)

Solar Steam Generator:

SOLARStm[so]: Steam flow from solar thermal unitSOLARo[so]: Binary variable of solar thermal unit

Steam Turbine Generator:

STGStm[iεSTG]: Steam flow through the STG.STGPwr[iεSTG]: Power generation from the STG,STGNo[iεSTG]: Number of installations of the STG.

Condensing Steam Turbine Generator:

CSTGStm[iεCSTG]: Steam flow rate through CSTG,CSTGPwr[iεCSTG]: Power generated from CSTG.CSTGDuty[iεCSTG]: Duty of CSTG condenser.CSTGNo[iεCSTG]: Number of installed units of CSTG of the given specs.

Switchable Motors to Process Steam Turbines:

MSwitchOnOff[iεMSwitch]: binary variable (0/1) of a switchable motorPSTSwitchStm[iεMSwitch]: steam flow to process steam turbines switchablewith motors

Breakover Station:

BOSStm[iεBOS]: Steam flow through the BOS.BOSNo[iεBOS]: Number of installed BOS units.

Condenser:

CONDStm[iεCOND]: Steam flowrate through the condenser.CODDuty[iεCOND]: Duty of the condenser.CONDNo[iεCOND]: Number of installed condenser units.

Condensate System:

SkimTankInFlow: Input flowrate to skim tank.SkimTankOutFlow: Output flowrate from skim tank.SkimTankOutEnth: Enthalpy of skim tank outlet.MUWtrFlow: Flow rate of makeup water to the system.

Dearator:

DEAStmFlow: Dearator team flow rate.DEAOutWtrFlow: Dearator output water flow rate.

Process Steam Generator:

PSGenProd[iεPST]: Steam production rate of process steam generator.

Boiler Feedwater System:

BFWFlow: Boiler feedwater flow rate.

Process Cooling Demand:

PCoolingDem[iεPCDem]: Determine optimal values of: steam for coolingdemand, water cooling, air-cooling and refrigeration cooling demands

Steam Headers:

Header Inlet Flow.

$\begin{matrix}{{{HDRIn}\lbrack h\rbrack} = {{{{HDRRet}\lbrack h\rbrack} + {{HDRBFW}\lbrack h\rbrack} + {\sum\limits_{{({b,h})} \in {BLRHDR}}{{{BLRSTM}\lbrack b\rbrack} \cdot {{BLRNo}\lbrack b\rbrack}}} + {\sum\limits_{{({{so}.h})} \in {SOLARHDR}}{{{SOLARSTM}\lbrack{so}\rbrack} \cdot {{SOLARNo}\lbrack{so}\rbrack}}} + {\sum\limits_{{({c.h})} \in {COGENHDR}}{{{COGENStm}\lbrack c\rbrack} \cdot {{COGENNo}\lbrack c\rbrack}}} + {\sum\limits_{{({x.h})} \in {STGOutHDR}}{{{STGStm}\lbrack s\rbrack} \cdot ( {1 - {{STGLoss}\lbrack s\rbrack}} ) \cdot {{STGNo}\lbrack s\rbrack}}} + {\sum\limits_{{({b.h})} \in {BOSOut}}{{{BOSStm}\lbrack b\rbrack} \cdot ( {1 - {{BOSLoss}\lbrack b\rbrack}} ) \cdot {{BOSNo}\lbrack b\rbrack}}} + {\sum\limits_{{({p.h})} \in {PSTOutHDR}}{{{PSTStm}\lbrack p\rbrack} \cdot ( {1 - {{PSTLoss}\lbrack p\rbrack}} )}} + {\sum\limits_{{({p.h})} \in {PSGenHDR}}{{PSGenProd}\lbrack p\rbrack}}} \in {HDR}}} & {\forall h}\end{matrix}$

Header Outlet Flow.

$\begin{matrix}{{{HDROut}\lbrack h\rbrack} = {{{\sum\limits_{{({x.h})} \in {SDemHDR}}{{HDRDem}\lbrack h\rbrack}} + {\sum\limits_{{({x.h})} \in {STGInHDR}}{{{STGStm}\lbrack s\rbrack} \cdot {{STGNo}\lbrack s\rbrack}}} + {\sum\limits_{{({x.h})} \in {STGInHDR}}{{PSTSwitchStm} \cdot {{PSTNo}\lbrack s\rbrack}}} + {\sum\limits_{{({c.h})} \in {CSTGHDR}}{{{CSTGStm}\lbrack c\rbrack} \cdot {{CSTGNo}\lbrack c\rbrack}}} + {\sum\limits_{{({s.h})} \in {PSTInHDR}}{{{PSTStm}\lbrack s\rbrack} \cdot {{PSTNo}\lbrack s\rbrack}}} + {\sum\limits_{{({b.h})} \in {BOSIn}}{{{BOSStm}\lbrack b\rbrack} \cdot {{BOSNo}\lbrack b\rbrack}}} + {\sum\limits_{{({c.h})} \in {CONDHDR}}{{{CONDStm}\lbrack c\rbrack} \cdot {{CONDNo}\lbrack c\rbrack}}} + {\sum\limits_{h \in {DEAStmHDR}}{DEAStmFlow}} + {\sum\limits_{{({p.h})} \in {PSTInHDR}}{{PSTDem}\lbrack p\rbrack}}} \in {HDR}}} & {\forall h}\end{matrix}$

Material Balance

HDRIn[h]·(1−HDRLoss[h])=HDROut[h] ∀hεHDR

Energy Balance.

$\begin{matrix}{{{{HDRIn}\lbrack h\rbrack} \cdot {{HDREnth}\lbrack h\rbrack}} = {{{{{HDRRet}\lbrack h\rbrack} \cdot {{HDREnth}\lbrack h\rbrack}} + {{{HDRBFW}\lbrack h\rbrack} \cdot {{BFWEnth}\lbrack h\rbrack}} + {{{HDREnth}\lbrack h\rbrack}~\underset{{({{xo},h})} \in {SOLARHDR}}{\Sigma}{{{SOLARSTM}\lbrack{so}\rbrack} \cdot {{SOLARNo}\lbrack{so}\rbrack}}} + {{{{HDREnth}\lbrack h\rbrack} \cdot \underset{{({b,h})} \in {BLRHDR}}{\Sigma}}{{{BLRSTM}\lbrack b\rbrack} \cdot {{BLRNo}\lbrack b\rbrack}}} + {\underset{{({s.h})} \in {STGInHDR}}{\Sigma}{{PSTSwitchStm} \cdot {{PSTNo}\lbrack s\rbrack} \cdot {PSTEnthOut}}} + {{{{HDREnth}\lbrack h\rbrack} \cdot \underset{{({e.h})} \in {COGENHDR}}{\Sigma}}{{{COGENStm}\lbrack c\rbrack} \cdot {{COGENNo}\lbrack c\rbrack}}} + {\underset{{({s.h})} \in {STGOutHDR}}{\Sigma}{{{STGStm}\lbrack s\rbrack} \cdot ( {1 - {{STGLoss}\lbrack s\rbrack}} ) \cdot {{STGNo}\lbrack s\rbrack} \cdot {{STGEnthOut}\lbrack s\rbrack}}} + {\underset{{({b.h})} \in {BOSOut}}{\Sigma}{{{BOSStm}\lbrack b\rbrack} \cdot ( {1 - {{BOSLoss}\lbrack b\rbrack}} ) \cdot {{BOSNo}\lbrack b\rbrack} \cdot {{BOSEnth}\lbrack b\rbrack}}} + {\underset{{({p.h})} \in {PSTOutHDR}}{\Sigma}{{{PSTDem}\lbrack p\rbrack} \cdot {( {1 - {{PSTLoss}\lbrack p\rbrack}} ).{{PSSTEnth}\lbrack p\rbrack}}}} + {\underset{{({p.h})} \in {PSGenHDR}}{\Sigma}{{{PSGenProd}\lbrack p\rbrack} \cdot {{PSGenEnth}\lbrack p\rbrack}}}} \in {HDR}}} & {\forall h}\end{matrix}$

Boilers:

Material Balance.

BLRBFW[b]·(1−BLRLoss)=BLRStm[b]+BLRBL[b] ∀bεBLR

Boiler Blowdown Calculation.

BLRBD[b]·(BLRSS[b]−1)=BLRStm[b] ∀bεBLR

Boiler Fuel Use Calculation.

BLRFuel[b]=BLRc0[b]+BLRc1[b]·BLRStm[b]+BLRc2·BLRStm[b] ² ∀bεBLR

Boiler Capacity Constraints.

BLRStm[b]≧BLRMin[b]·BLROn[b] ∀bεBLR

BLRStm[b]≦BLRCap[b]·BLROn[b] ∀bεBLR

Boiler Steam Reserves.

$\underset{b \in {BLR}}{\Sigma}{{{BLROn}\lbrack b\rbrack} \cdot ( {{{BLRCap}\lbrack b\rbrack} - {{BLRStm}\lbrack b\rbrack}} ) \cdot {{BLRNo}\lbrack b\rbrack}}$

Cogeneration:

Steam Production.

COGENStm[c]=COGENPwr[c]·COGENStmRatio[c] ∀cεCOGEN

Material Balance.

COGENBFW[c]·(1−COGENLoss)=COGENStm[c]+COGENBD[c] ∀cεCOGEN

Blowdown Calculation.

COGENBD[c]·(COGENCC[c]−1)=COGENStm[c] ∀cεCOGEN

Cogen Fuel Use.

$\begin{matrix}{{{COGENFuel}\lbrack c\rbrack} = \{ {\begin{matrix}{{{{COGENc}\; {0\lbrack c\rbrack}} + {{COGENc}\; {{1\lbrack c\rbrack} \cdot {{COGENPwr}\lbrack c\rbrack}}} + {{COGENc}\; {{2\lbrack c\rbrack} \cdot {{COGENPwr}\lbrack c\rbrack}^{2}}}},} & {{{if}\mspace{14mu} {{COGENStm}\lbrack c\rbrack}} > 0} \\{0,} & {{{if}\mspace{14mu} {{COGENStm}\lbrack c\rbrack}} = 0}\end{matrix} \in {COGEN}} } & {\forall c}\end{matrix}$

Capacity Constraints.

COGENPwr[c]≧COGENMin[c]·COGENOn[c] ∀cεCOGEN

COGENPwr[c]≦COGENCap[c]·COGENOn[c] ∀cεCOGEN

Solar Thermal Steam Generation/Heating:

Material Balance:

SOLARBFW[so]·(1−SOLARLoss)=SOLARStm[so] ∀soεSOLAR

Steam Production:

SOLARStm[SO]=SOLARon[so]·SOLAREff[so]·SOLARRad ∀soεSOLAR

Steam Turbine Generator:

Power Generation calculation.

STGPwr[s]·3412=STGStm[s]·(STGEnthIn[s]−STGEEnthOut[s]) ∀sεSTG

Capacity.

STGStm[s]≧0 ∀sεSTG

STGStm[a]≦STGCap[s] ∀sεSTG

Condensing Steam Turbine Generator:

Power Generation Calculation

CSTGPwr[c]·3412=CSTGStm[c]·(CSTGEnthIn[c]−CSTGEnthOut[c]) ∀cεCSTG

Capacity.

CSTGStm[c]≧0 ∀cεCSTG

CSTGStm[c]≦CSTGCap[c] ∀cεCSTG

Steam Demands:

Demand Ranges in a Header for Each (2 Hrs):

PSDem[h]≧HDRMinDem ∀hεHDR

PSDem[h]≦HDRMaxDem ∀hεHDR

Note:

PSDem=Σ_(i=0) ²⁴PSDem_(Indst)+PSDem_(hospital)+PSDem_(commercial)

Breakover Stations:

Capacity.

BOSStm[b]≧0 ∀bεBOS

BOSStm[b]≦BOSCap[b] ∀bεBOS

Condenser:

Duty Calculation

CONDDuty[c]·1000=CONDStm[c]·CONDEnthDuty[c] ∀cεCOND

Capacity.

CONDStm[c]≧0 ∀cεCOND

CONDStm[c]≦CONDCap[c] ∀cεCOND

Skim Tank:

Material Balance.

${{SkimTankInFlow} \cdot ( {1 - {SkimTankLoss}} )} = {{SkimTankOutFlow}\begin{matrix}{{SkimTankInFlow} = {CondRetFlow}} \\{{+ {MUWtrFlow}}} \\{{{+ \underset{c \in {CSTG}}{\Sigma}}{{{CSTGStm}\lbrack c\rbrack} \cdot ( {1 - {{CSTGLoss}\lbrack c\rbrack}} ) \cdot {{CSTGNo}\lbrack c\rbrack}}}} \\{{{+ \underset{c \in {COND}}{\Sigma}}{{{CONDStm}\lbrack c\rbrack} \cdot ( {1 - {{CONDLoss}\lbrack c\rbrack}} ) \cdot {{CONDNo}\lbrack c\rbrack}}}}\end{matrix}}$

Energy Balance.

${{{SkimTankOutFlow} \cdot {Ski}}\; {mTankOutEnth}} = {{{CondRetFlow} \cdot {CondRetTargEnth}} + {{MUWtrFlow} \cdot {MUWtrEnth}} + {\underset{c \in {CSTG}}{\Sigma}{{{CSTGStm}\lbrack c\rbrack} \cdot ( {1 - {{CSTGLoss}\lbrack c\rbrack}} ) \cdot {{CSTGWtrEnth}\lbrack c\rbrack} \cdot {{CSTGNo}\lbrack c\rbrack}}} + {\underset{c \in {COND}}{\Sigma}{{{CONDStm}\lbrack c\rbrack} \cdot ( {1 - {{CONDLoss}\lbrack c\rbrack}} ) \cdot {{CONDEnth}\lbrack c\rbrack} \cdot {{CONDNo}\lbrack c\rbrack}}}}$

Deaerator:

Material Balance.

(SkimTankOutFlow+DEAStmFlow)·(1−DEALoss)=DEAVentFlow+DEAOutWtrFlow

Energy Balance.

SkimTankOutFlow·SkimTankOutEnth+DEAStmFlow·DEAStmEnth=DEAVentFlow·DEAVentEnth+DEAOutWtrFlow·DEAOutWtrEnth

Boiler Feedwater

Material Balance.

${BFWLow} = {{\underset{h \in {HDR}}{\Sigma}{{HDRBFW}\lbrack h\rbrack}} + {\underset{b \in {BLR}}{\Sigma}{{{BLRBFW}\lbrack b\rbrack} \cdot {{BLRNo}\lbrack b\rbrack}}} + {\underset{c \in {COGEN}}{\Sigma}{{{COGEN}\lbrack c\rbrack} \cdot {{COGENNo}\lbrack c\rbrack}}}}$BFWFow = DEAOutWtrFlow ⋅ (1 − BFWLoss)

Power:

Total Power Generation Calculation.

${TotPwrGen} = {{\underset{c \in {COGEN}}{\Sigma}{{{COGENPwr}\lbrack c\rbrack} \cdot {{COGENNo}\lbrack c\rbrack}}} + {\underset{s \in {STG}}{\Sigma}{{{STGPwr}\lbrack s\rbrack} \cdot {{STGNo}\lbrack s\rbrack}}} + {\underset{{ms} \in {STG}}{\Sigma}{MSwitchMWToPST}} + {\underset{c \in {CSTG}}{\Sigma}{{{CSTGPwr}\lbrack c\rbrack} \cdot {{CSTGNo}\lbrack c\rbrack}}}}$

Satisfy Power Requirements.

TotPwrGen+TotPwrImp−TotPwrExp≧TotPwrDem,

Note:

TotPwrDem=Σ_(i=0)²⁴PwrDem_(Indsc)+PwrDem_(hospital)+PwrDem_(comrcial)+PwrDem_(gerid)

Exported Power Calculation.

${TotPwrExp} = \{ \begin{matrix}{{{TotPwrGen} + {TotPwrImp} - {TotPwrDem}},} & {{{{if}\mspace{14mu} {TotPwrGen}} + {TotPwrImp}} > {TotPwrDem}} \\{0,} & {Otherwise}\end{matrix} $

Constraints

Process Cooling Demand:

${PCoolongDem} = {{\underset{{({LPC})} \in {PCoolingDem}}{\Sigma}{{AirCDuty}\lbrack l\rbrack}} + {\underset{{({LPC})} \in {PCoolingDem}}{\Sigma}{{WtrCDuty}\lbrack l\rbrack}} + {\underset{{({LPC})} \in {PCoolingDem}}{\Sigma}{{RefDutyR}\lbrack i\rbrack}}}$

Fuel:

Total Fuel Use.

${TotFuelUse} = {{\underset{b \in {BLR}}{\Sigma}{{{BLRFuel}\lbrack b\rbrack} \cdot {{BLRNo}\lbrack b\rbrack}}} + {\underset{c \in {COGEN}}{\Sigma}{{{COGENFuel}\lbrack c\rbrack} \cdot {{COGENNo}\lbrack c\rbrack}}}}$

Steam Reserves:

Maximum Steam Generation from a Boiler Unit.

${MaxBlrStm} = {\max\limits_{b \in {BLR}}\{ {{{BLRStm}\lbrack b\rbrack} \cdot {{BLRNo}\lbrack b\rbrack}} \}}$

Maximum Steam Generation from a Cogen Unit.

${MaxCogenStm} = {\max\limits_{c \in {COGEN}}\{ {{{COGENStm}\lbrack b\rbrack} \cdot {{COGENNo}\lbrack b\rbrack}} \}}$

Required Steam Reserves Calculation.

RequiredStmRes=max(MaxBlrStm,MaxCogenStm)

Condensate Steam Reserves Calculation.

${CondStemRes} = {{\underset{c \in {CSTG}}{\Sigma}{{{CSTGStm}\lbrack c\rbrack} \cdot ( {1 - {{CSTGLoss}\lbrack c\rbrack}} ) \cdot {{CSTGNo}\lbrack c\rbrack}}} + {\underset{c \in {COND}}{\Sigma}{{{CONDStm}\lbrack c\rbrack} \cdot ( {1 - {{CONDLoss}\lbrack c\rbrack}} ) \cdot {{CONDNo}\lbrack c\rbrack}}}}$

Steam Reserves Calculation.

StemRes=max(RequiredStmRes−CondStmRes,0)

Economics Calculation:

The model can advantageously solve the problem in two steps, one step tofind the optimum configuration design point of view, which will be basedon the maximum demands values. The next step is to optimally operate theutilities complex model to solve all demands for each time step (i).

Total Design Calculation:

${TotCost} = {{( {{{TotFuelUse} \cdot {PriceFuel}} + {{MUWtrFlow} \cdot {PriceMUWtr}} + {{TotPwrImp} \cdot {PriceImpPwr}} - {{TotPwrExp} \cdot {PriceExpPwr}}} )\text{/}1000} + {\underset{b \in {BLR}}{\Sigma}{{{BLRNo}\lbrack b\rbrack} \cdot {{BLRPrice}\lbrack b\rbrack}}} + {\underset{h \in {hdr}}{\Sigma}{{{Hdr}\lbrack h\rbrack} \cdot {{HdrPrice}\lbrack h\rbrack}}} + {\underset{c \in {COGEN}}{\Sigma}{{{COGENNo}\lbrack c\rbrack} \cdot {{COGENPrice}\lbrack c\rbrack}}} + {\underset{{s\; 0} \in {SOLAR}}{\Sigma}{{{SOLARNo}\lbrack s\rbrack} \cdot {{SOLARPrice}\lbrack s\rbrack}}} + {\underset{s \in {STG}}{\Sigma}{{{STGNo}\lbrack s\rbrack} \cdot {{STGPrice}\lbrack s\rbrack}}} + {\underset{c \in {CSTG}}{\Sigma}{{{CSTGNo}\lbrack c\rbrack} \cdot {{CSTGPrice}\lbrack c\rbrack}}} + {\underset{b \in {BOS}}{\Sigma}{{{BOSNo}\lbrack b\rbrack} \cdot {{BOSPrice}\lbrack b\rbrack}}} + {\underset{c \in {COND}}{\Sigma}{{{CONDNo}\lbrack c\rbrack} \cdot {{CONDPrice}\lbrack c\rbrack}}} + {\underset{{({LPC})} \in {PCoolingDem}}{\Sigma}{{{AirCDuty}\lbrack l\rbrack} \cdot {{AirCPrice}\lbrack l\rbrack}}} + {\underset{{({LPC})} \in {PCoolingDem}}{\Sigma}{{{WtrCDuty}\lbrack i\rbrack} \cdot {{WtrCPrice}\lbrack i\rbrack}}} + {\underset{{({LPC})} \in {PCoolingDem}}{\Sigma}{{{RefDutyR}\lbrack i\rbrack} \cdot {{RefCPrice}\lbrack i\rbrack}}}}$

Objective:

The objective is to minimize the total operating cost, which can beexpressed as: minimizeTotCost

Note: This is done for the maximum demand over the range of whole timesteps to find the most optimum design configuration.

Total Operating Cost Calculation (Operational Optimization):

$= {\underset{t \in {Interval}}{\overset{TotOperCost}{\Sigma}}( {{( {{{TotFuelUse} \cdot {PriceFuel}} + {{MUWtrFlow} \cdot {PriceMUWtr}} + {{TotPwrImp} \cdot {PriceImpPwr}} - {{TotPwrExp} \cdot {PriceExpPwr}}} )\text{/}1000} + {\underset{b \in {BLR}}{\Sigma}{{{BLRNo}\lbrack b\rbrack} \cdot {{BLRPrice}\lbrack b\rbrack}}} + {\underset{h \in {hdr}}{\Sigma}{{{Hdr}\lbrack h\rbrack} \cdot {{HdrPrice}\lbrack h\rbrack}}} + {\underset{c \in {COGEN}}{\Sigma}{{{COGENNo}\lbrack c\rbrack} \cdot {{COGENPrice}\lbrack c\rbrack}}} + {\underset{{s\; 0} \in {SOLAR}}{\Sigma}{{{SOLARNo}\lbrack s\rbrack} \cdot {{SOLARPrice}\lbrack s\rbrack}}} + {\underset{s \in {STG}}{\Sigma}{{{STGNo}\lbrack s\rbrack} \cdot {{STGPrice}\lbrack s\rbrack}}} + {\underset{c \in {CSTG}}{\Sigma}{{{CSTGNo}\lbrack c\rbrack} \cdot {{CSTGPrice}\lbrack c\rbrack}}} + {\underset{b \in {BOS}}{\Sigma}{{{BOSNo}\lbrack b\rbrack} \cdot {{BOSPrice}\lbrack b\rbrack}}} + {\underset{c \in {COND}}{\Sigma}{{{CONDNo}\lbrack c\rbrack} \cdot {{CONDPrice}\lbrack c\rbrack}}} + {\underset{{({LPC})} \in {PCoolingDem}}{\Sigma}{{{AirCDuty}\lbrack l\rbrack} \cdot {{AirCPrice}\lbrack l\rbrack}}} + {\underset{{({LPC})} \in {PCoolingDem}}{\Sigma}{{{WtrCDuty}\lbrack i\rbrack} \cdot {{WtrCPrice}\lbrack i\rbrack}}} + {\underset{{({LPC})} \in {PCoolingDem}}{\Sigma}{{{RefDutyR}\lbrack i\rbrack} \cdot {{RefCPrice}\lbrack i\rbrack}}}} )}$

Where, i: is the time interval (h) at which the problem will be solvedfor each interval, start with maximum demand, and then solve for eachtime step.

Objective:

The objective is to minimize the total operating cost, which can beexpressed as:

minimize TotOperCos

Note: This is done for the whole time steps to find the most optimumoperation modes.

That claimed is:
 1. A method of providing enhanced energy efficiency andreduced greenhouse gases for an eco-industrial park through applicationof spatial and temporal waste heating and cooling energy integration,the method comprising the steps of: identifying a plurality offunctional areas for an eco-industrial park, the plurality of functionalareas comprising a plurality of industrial functional areas and one ormore non-industrial functional areas in adjacent geographical locations,each of the plurality of industrial functional areas containing one ormore process streams comprising one or more of the following: one ormore hot process streams to be cooled and one or more cold processstreams to be heated, each of the one or more non-industrial functionalareas containing one or more of the following: one or more hot streamsand one or more cold streams; identifying a plurality of significantheating and cooling tasks for each significant time-dependent andnon-time-dependent industrial and non-industrial activity within theeco-industrial park; responsive to the identified functional areas andidentified significant heating and cooling tasks, determining one ormore inter-time zone thermal energy integration thermal targets and oneor more intra-time zone thermal energy integration thermal targets; andresponsive to the determined one or more inter-time zone thermal energyintegration thermal targets and one or more intra-time zone thermalenergy integration thermal targets, performing inter-time zone thermalenergy integration matching comprising identifying one or moreinter-time zone thermal energy integration matching solutions across aplurality of time zones to substantially satisfy a thermal load to beintegrated via inter-time zone thermal energy integration.
 2. A methodas defined in claim 1, wherein the plurality of time zones includes atleast three times zones, the method further comprising the step of:generating one or more technically viable eco-industrial park heatexchange system design alternatives responsive to the identified one ormore inter-time zone thermal energy integration matching solution.
 3. Amethod as defined in claim 1, wherein the plurality of time zonesincludes at least three times zones, the method further comprising thestep of: generating at least one technically viable energy efficienteco-industrial park alternative that satisfies the eco-industrial parkthermal energy and steam utilities demands for the plurality of timezones as well as rendering a corresponding approximately optimaloperating scenario at each specific time-zone.
 4. A method as defined inclaim 1, wherein the step of determining one or more inter-time zonethermal energy integration targets includes analyzing duration of theplurality of time zones as an optimization variable.
 5. A method asdefined in claim 1, wherein boundaries of the plurality of time zonesare defined by a smallest heating or cooling time duration for anysignificant candidate activity in the eco-industrial park underanalysis.
 6. A method as defined in claim 1, wherein the steps ofdetermining one or more inter-time zone thermal energy integrationthermal targets and intra-time zone thermal energy integration thermaltargets comprises the steps of: identifying total supply and demandthermal energy loads at each of a plurality of temperature intervals;identifying inter-time zone surplus thermal energy load between each ofthe plurality of time zones at each of the plurality of temperatureintervals; identifying total supply and demand thermal energy loads ateach of the plurality of time zones at each of the plurality oftemperature intervals; and identifying a thermal energy load to beintegrated via inter-time zone thermal energy integration and intra-timezone matching.
 7. A method as defined in claim 1, wherein the steps ofdetermining inter-time zone thermal energy integration thermal targetsand intra-time zone thermal energy integration thermal targets, includesthe steps of: identifying total supply and demand at each temperatureinterval; identifying the supply and demand and surplus of eachfunctional area; and identifying the global minimum heating and coolingneeds for the dependent and non-time dependent industrial andnon-industrial activities.
 8. A method as defined in claim 1, whereinthe step of identifying the one or more inter-time zone thermal energyintegration matching solutions comprises the step of: identifying bestand second best matching solutions from the one or more potentialinter-time zone thermal integration matching solutions.
 9. A method asdefined in claim 8, further comprising the step of: selecting a matchingsolution either substantially satisfying an optimal one of the one ormore inter-time zone thermal energy integration thermal targets or adesired level of one or more energy targets for heating utility, coolingutility, or both heating utility and cooling utility selected by adecision-maker.
 10. A method as defined in claim 1, wherein the step ofperforming inter-time zone thermal energy integration matching isperformed prior to performing intra-time zone thermal energy integrationmatching, the method further comprising the step of: performingintra-time zone thermal energy integration matching.
 11. A method asdefined in claim 1, wherein the step of identifying one or moreinter-time zone thermal energy integration matching solutions comprisesperforming inter-time zone thermal energy integration matching, toinclude temporally and spatially matching batch process streams withbatch process streams and batch process streams with continuous processstreams.
 12. A method as defined in claim 1, wherein the step ofidentifying one or more inter-time zone thermal energy integrationmatching solutions, comprises: matching waste heat of multiple hotprocess streams within each functional area with multiple hot processstreams of each other functional area of a plurality of functionalareas; and the matching of the waste heat including separately matchingfor each of a plurality of different steam levels.
 13. A method asdefined in claim 1, wherein the step of performing inter-time zonethermal energy integration matching is accomplished while simultaneouslyconsidering both inter-time-zones and inter-area thermal energyintegration; and wherein the inter-time zone thermal energy integrationmatching includes identifying a plurality of the functional areas to beincluded in one or more of the functional areas to be excluded from thematching solution.
 14. A method as defined in claim 1, wherein the stepof i performing inter-time zone thermal energy integration matching isaccomplished while simultaneously considering both inter-time zone andinter-area integration, comprising a plurality of the following:performing hybrid matching techniques comprising: direct and indirectarea integration, hot-to-hot process-to-process matching, cold-to-coldunit process-to-process matching, and process identities switching;performing process stream rescheduling; performing process energystorage; and performing process stream heat capacity flowratemanipulation using variable speed drivers.
 15. A method as defined inclaim 1, further comprising the steps of: identifying media of thethermal load to be integrated via inter-time zone thermal energyintegration, the media comprising one or more of the following: thermalenergy storage, rescheduling of activities or process streams, andchanging of process stream flow rates; and identifying one or moreintra-time zone thermal energy integration matching solutions for eachof the plurality of time zones and across a plurality of the functionalareas having one or more tasks operating within the respective time zonewhen having more than one functional area associated therewith.
 16. Amethod as defined in claim 15, wherein the step of identifying one ormore intra-time zone thermal energy integration matching solutions,comprises the steps of: identifying best and the second best matchingsolutions among the hot and cold process streams in the eco-industrialpark for spatial energy integration, and identifying best and secondbest matching solutions among each of the plurality of time-zones fortemporal energy integration and greenhouse gas emissions reduction foroptimal synthesis or retrofit of the eco-industrial park,
 17. A methodas defined in claim 15, wherein the steps of identifying one or moreinter-time zone thermal integration matching solutions and identifyingone or more intra-time zone thermal integration matching solutionsincludes identifying functional areas to consider for integration andothers to neglect as having an in substantial energy values; wherein themethod further comprises generating a plurality of technically viableenergy efficient eco-industrial park alternatives that satisfieseco-industrial park utilities demands during each of the plurality oftime zones as well as rendering a corresponding approximately optimaloperating scenario at each specific time-zone; and wherein the step ofgenerating a plurality of technically viable energy efficienteco-industrial park alternatives comprises identifying a scheme ofinter-area integration, the scheme of inter-area integration comprisingdirect, indirect or hybrid inter-area integration, and when eitherindirect or hybrid are utilized, identifying indirect medium, theindirect medium comprising water, steam, hot oil, or a combinationthereof.
 18. A method as defined in claim 1, wherein the one or more hotprocess streams comprise a plurality of hot process streams, and whereina subset of the plurality of hot process streams: have different startup or shut down times, work intermittently at partial loads, or haveseasonal dependent operating conditions.
 19. A method as defined inclaim 1, further comprising the steps of: identifying one or more bestenergy and greenhouse gas emission reduction targets; systematicallyidentifying when direct inter-time integration is best utilized and isthe only option to reach the best energy and greenhouse gas emissionsreductions' targets; and systematically identifying when indirectintra-time integration alone can be used to reach the best energy andgreenhouse gas emissions reduction targets.
 20. A method as defined inclaim 1, wherein the plurality of industrial functional areas comprisingone or more of the following: a plurality of spatial zones, a pluralityof blocks, a plurality of facilities, a plurality of plants, and aplurality of batch and continuous process units; wherein the one or morenon-industrial functional areas comprise one or more of the following:one or more housing compounds, one or more hospitals, one or morelaundry facilities, and one or more facilities having large capacitydishwashing units; and wherein the one or more hot streams comprised bythe one or more non-industrial functional areas comprise one or more ofthe following: one or more waste streams emanating from the one or morehousing compounds, the one or more hospitals, the one or more laundryfacilities, and the one or more facilities having large capacitydishwashing.
 21. A method as defined in claim 1, further comprising thesteps of: extracting operational data for the plurality of significantheating and cooling tasks, the operational data comprising duration,process stream initial type, supply temperature, target temperature, andheat capacity flow rate; constructing a virtual time-space schematic forthe eco-industrial park heating and cooling tasks to identify time zoneboundaries; providing a Time-Temperature-Duty-Diagram to establish afunctional area supply-demand cascade from heating and cooling tasksrespectively at each of a plurality of temperature intervals;calculating a total supply and demand at each temperature interval, thestep of calculating comprising cascading the functional areas supply anddemand in time; calculating one or more of the following: inter-timezones energy load storage, rescheduling requirements, and streamflowrate modifications among each of the plurality of time zones for theeco-industrial park; and calculating global minimum heating and coolingneeds for the dependent and non-dependent industrial and non-industrialactivities of the eco-industrial park.
 22. A method as defined in claim1, wherein the step of identifying one or more inter-time zone thermalenergy integration matching solutions comprises constructing a problemwide time-temperature duty diagram, comprising the steps of: forming aglobal Cold Composite Line (gCCL) to summarize heating energyrequirements for substantially all significant zones, blocks,facilities, plants and process streams in each of a plurality of timezones at each of a plurality of temperature intervals; forming a globalHot Composite Line (gHCL) summarize for cooling energy requirements forsubstantially all the zones, blocks, facilities, plants and processes'streams in each time zone at each of the plurality of temperatureintervals; displaying a problem-wide pinch location; displaying indiciaof cold composite and hot composite thermal loads above the problem-widepinch temperature for each individual time zone; displaying indicia of acold composite and hot composite thermal loads below the problem-widepinch temperature for each individual time zone; displaying indicia oftotal surplus heating load for each time zone for above the problem widepinch temperature and for below the problem wide pinch temperature;displaying indicia of a global cooling energy utility requirement;displaying indicia of total surplus cooling load for each time zone forabove the problem-wide pinch temperature and for below the problem-widepinch temperature; and displaying indicia of a global heating energyutility requirement.
 23. A method as defined in claim 1, wherein thestep of performing inter-time zone thermal energy integration matchingcomprises performing hybrid inter-time zone inter-area thermal energyintegration matching, comprising the steps of: predefining a global ColdComposite Line (gCCL) accounting for heat energy requirements forsubstantially all significant zones, blocks, facilities, plants andprocesses' streams comprised by the plurality of functional areas ineach of a plurality of time zones at each of a plurality of temperatureintervals; predefining a global Hot Composite Line (gHCL) accounting forcooling energy requirements for substantially all the zones, blocks,facilities, plants and processes' streams in each time zone at each ofthe plurality of temperature intervals; identifying thermal loads to beintegrated via intra-time integration and inter-time integration;conducting inter-time zone energy matching; defining media of thethermal load to be integrated via the inter-time zone thermal energyintegration; and conducting intra-time zone intra-area energy matchingfor each of the plurality of time zones, to include the steps of:initiating the intra-time intra-area matching via de-lumping of eachpredetermined time zone specific global cold composite line and eachpredefined time zone specific global hot composite line into itsfunctional area structures from largest to smallest, and conducting theintra-time intra-area matching.
 24. A method as defined in claim 1,further comprising the steps of: determining global minimum heatingenergy utility and global minimum cooling energy utility requirementsunder all reasonably probable combinations of process-specificmodifications and stream-specific ΔT_min in an acceptable user definedrange across space and time; locating problem wide pinch interval andpinch location controlling stream or streams; determining energy targetsfor inter-time inter- and intra-space energy integration and intra-timeinter- and intra-space energy integration; receiving decision makerselection identifying desired level of energy targets for one or more ofthe following: heating utility, cooling utility, and both heating andcooling utilities; receiving user input of absolutely constrained andforbidden functional area and process streams matching whereby arespective thermal load must be satisfied via indirect integration;collapsing operational data intervals when operational data is providedin interval form to locate the problem wide best for desired pinchtemperature, the pinch-temperature location controlling process, and thebest process stream changes as well as streams-specific ΔT_min in theacceptable user defined range; and wherein the step of identifying oneor more inter-time zone thermal energy integration matching solutionscomprises the step of determining one or more best possible matchesamong the time zones and the functional areas.
 25. A method as definedin claim 1, further comprising the step of: generating a plurality oftechnically viable energy efficient eco-industrial park alternativesthat satisfies eco-industrial park utilities demands during each of theplurality of time zones as well as rendering a correspondingapproximately optimal operating scenario at each specific time-zone. 26.A method as defined in claim 25, wherein the step of generating aplurality of technically viable energy efficient eco-industrial parkalternatives, comprises the steps of: identifying best generation andallocation of steam energy utilities, and synthesizing the combined heatand power utility system that satisfies the eco-industrial parkutilities demands during each of the plurality of time zones as well asrendering its best operating scenario at each specific time-zone.
 27. Amethod as defined in claim 25, wherein the step of generating aplurality of technically viable energy efficient eco-industrial parkalternatives, comprises the steps of: calculating required steam supplyand demand levels and loads for the plurality of functional areas;establishing a virtual functional area steam supply-demand cascade inspace from steam supply and demand loads respectively at each aplurality of steam levels; calculating total supply and demand loads ateach steam level responsive to the cascade of the functional areas steamsupply and demand in space; defining functional area arrangements whichminimize steam transportation; and identifying amounts of steam to betransferred from one functional area to another to achieve globalminimum steam demand before steam letdowns.
 28. A method as defined inclaim 25, wherein the step of generating a plurality of technicallyviable energy efficient eco-industrial park alternatives, comprises thestep of performing a domino affect low-pressure steam sharing targetingprocess, comprising the steps of: allocating low-pressure steam tofunctional areas in a mosaic starting with a central power plant or maincogeneration plant then followed by functional areas arranged in theform of demand supply demand and ending by functional area demand, steambeing transferred from one functional area to the next functional areaprimarily or completely only to avoid long distances and steamcondensation, a plurality of the functional areas acting as a conduit topass steam from a supplying functional area to another functional areawithout requiring steam from the supplying functional area; highlightingin-process modifications that can be performed to enhance process orfunctional area capability in producing more steam or whose status canbe changed from demanding to supplying or vice versa; and arranging thefunctional areas by their geographical locations to substantially reducesteam travel distances and steam condensation.
 29. A method of providingenhanced energy efficiency and reduced greenhouse gases for aneco-industrial park through application of spatial and temporal wasteheating and cooling energy integration, the method comprising the stepsof: identifying a plurality of functional areas for an eco-industrialpark, the plurality of functional areas comprising a plurality ofindustrial functional areas and one or more non-industrial functionalareas in adjacent geographical locations, the plurality of industrialfunctional areas comprising one or more of the following: a plurality ofspatial zones, a plurality of blocks, a plurality of facilities, aplurality of plants, and a plurality of batch and continuous processunits, each of the plurality of industrial functional areas containingone or more process streams comprising one or more of the following: oneor more hot process streams to be cooled and one or more cold processstreams to be heated, each of the one or more non-industrial functionalareas containing one or more of the following: one or more hot streamsand one or more cold streams; identifying at least substantially allsignificant heating and cooling tasks for each significanttime-dependent and non-time-dependent industrial and non-industrialactivities within the eco-industrial park; responsive to the identifiedfunctional areas and identified significant heating and cooling tasks,determining one or more inter-time zone thermal energy integrationthermal targets and one or more intra-time zone thermal energyintegration thermal targets; responsive to the one or more inter-timezone thermal energy integration thermal targets and one or moreintra-time zone thermal energy integration thermal targets, identifyingone or more potential inter-time zone thermal energy integrationmatching solutions across a plurality of time zones and a plurality ofthe functional areas within each time zone to substantially satisfy athermal load to be integrated via inter-time zone thermal energyintegration; identifying one or more intra-time zone thermal energyintegration matching solutions for each of the plurality of time zonesand across a plurality of the functional areas having one or more tasksoperating within the respective time zones when having more than onefunctional area associated therewith; and generating a plurality oftechnically viable energy efficient eco-industrial park alternativesthat satisfies eco-industrial park utilities demands during each of theplurality of time zones as well as rendering a correspondingapproximately optimal operating scenario at each specific time-zone. 30.A method of providing enhanced energy efficiency and reduced greenhousegases for an eco-industrial park through application of spatial andtemporal waste heating and cooling energy integration, the methodcomprising the steps of: identifying a plurality of functional areas foran eco-industrial park, the plurality of functional areas comprising aplurality of industrial functional areas and one or more non-industrialfunctional areas in adjacent geographical locations, the plurality ofindustrial functional areas comprising one or more of the following: aplurality of spatial zones, a plurality of blocks, a plurality offacilities, a plurality of plants, and a plurality of batch andcontinuous process units, each of the plurality of industrial functionalareas containing one or more process streams comprising one or more ofthe following: one or more hot process streams to be cooled and one ormore cold process streams to be heated, each of the one or morenon-industrial functional areas containing one or more of the following:one or more hot streams and one or more cold streams; identifying atleast substantially all significant heating and cooling tasks for eachsignificant time-dependent and non-time-dependent industrial andnon-industrial activities for the eco-industrial park; determining oneor more inter-time zone thermal energy integration thermal targets andone or more intra-time zone thermal energy integration thermal targets,comprising the steps of: identifying total supply and demand thermalenergy loads at each of a plurality of temperature intervals,identifying inter-time zone surplus thermal energy load between each ofthe plurality of time zones at each of the plurality of temperatureintervals, the plurality of time zones comprising at least three timezones, identifying total supply and demand thermal energy loads at eachof the plurality of time zones at each of the plurality of temperatureintervals, and identifying a thermal energy load to be integrated viainter-time zone thermal energy integration matching; identifying theglobal minimum heating and cooling needs for the dependent and non-timedependent industrial and non-industrial activities; receiving adecision-maker selection of a desired level or levels of thermal energyintegration for heating utility, cooling utility, or both heating andcooling utilities; identifying one or more potential inter-time zonethermal energy integration matching solutions across the plurality oftime zones and across a plurality of the functional areas having one ormore tasks operating within each of the respective time zones whenhaving more than one functional area associated therewith tosubstantially satisfy a thermal load or loads to be integrated viainter-time zone thermal energy integration, comprising the steps of:identifying best set and second best matching solutions from the one ormore potential inter-time zone thermal energy integration matchingsolutions, and selecting a matching solution substantially satisfyingthe desired level or levels of thermal energy integration selected bythe decision-maker; identifying media of the thermal load or loads to beintegrated via inter-time zone thermal energy integration, the mediacomprising one or more of the following: thermal energy storage,rescheduling of activities or process streams, and changing of processstream flow rates; identifying one or more intra-time zone thermalenergy integration matching solutions for each of the plurality of timezones and across a plurality of the functional areas having one or moretasks operating within the respective time zone when having more thanone functional area associated therewith, identifying best and thesecond best matching solutions among the hot and cold process streams inthe eco-industrial park for spatial energy integration, and identifyingbest and second best matching solutions among each of the plurality oftime-zones for temporal energy integration and greenhouse gas emissionsreduction for optimal synthesis or retrofit of the eco-industrial park,generating a plurality of technically viable energy efficienteco-industrial park alternatives having substantially similar physicalstructure and that satisfies eco-industrial park utilities demandsduring each of the plurality of time zones as well as rendering acorresponding approximately optimal operating scenario at each specifictime-zone, comprising the steps of: identifying best generation andallocation of energy utilities, and synthesizing the combined heat andpower utility system that satisfies the eco-industrial park utilitiesdemands during each of the plurality of time zones as well as renderingits best operating scenario at each specific time-zone.